Category: Our Posts

Reflections on the Skegg report pt.2

Dr Martin Lally

Director, Capital Financial Consultants Ltd

lallym@xtra.co.nz

In an earlier comment on the Skegg Report, I noted that the authors did not provide any empirical analysis in support of their conclusion that the elimination strategy should continue to be pursued in New Zealand.  However, in para 6, they did refer to a published paper that concluded that an elimination rather than a mitigation strategy has to date yielded the best outcomes for health (lower covid death rate), the economy (lower GDP losses) and civil liberties (lower average government restrictions). https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(21)00978-8/fulltext?

This paper compares the average death rates, GDP losses and restrictions on movement in the five OECD countries that consistently aimed for elimination with the rest that did not.  Everything is claimed to be better in the first group: a lower average death rate, smaller average GDP losses, and lower average restrictions on civil liberties.  Elimination is defined as “Maximum action to control SARS-CoV-2 and stop community transmission as quickly as possible.”  The five OECD countries claimed by them to have done so are Australia, Iceland, Japan, New Zealand, and South Korea.

This seems like the Holy Grail; if true, there would be no need for trading off liberty and GDP losses for lower covid deaths, and therefore no need for a cost-benefit analysis.  However, as usual, if it seems too good to be true, it isn’t.  The first problem is that the five countries that supposedly undertook the “maximum action to control SARS-CoV-2 and stop community transmission as quickly as possible” include Iceland, Japan and South Korea.  At the very least, maximum action to control covid as quickly as possible would involve border closures and lockdowns.  However, none of these three locked down and Iceland additionally did not even close its borders.

I conveyed this concern to the lead author of the paper (Professor Oliu-Barton), and he replied that their classification of countries relied in part on the ratio of the Stringency Index to the covid deaths during the period when the covid deaths were very low, with the five countries in question having high values for this ratio. This seemed rather subjective so I asked for further details to see if I could reproduce their result (which is fundamental to the credibility of scientific research).  I have yet to receive a reply to that.  Nevertheless, the following seems clear.

  1. The authors are not measuring the extent to which countries took the “maximum action to control covid” but are instead measuring how quicklygovernments reacted.  So, the conclusion of the paper (that elimination is superior to mitigation on all dimensions) is not supported by their analysis.  Instead, their analysis supports the conclusion (at most) that acting quickly produces the best outcomes on all dimensions.  Even this conclusion may be too strong because:
  2. The analysis in their paper considers only one possible variable that could explain deaths, economic losses and loss of liberties: how fast a government acts. They identify the five fastest movers in the OECD and find that these countries had on average much lower death rates than the other OECD countries (and other benefits), and then attribute this to them moving quickly.  However, had they instead conjectured (very reasonably) that being an island mattered, and identified the island nations amongst their OECD set, they would have found that these island nations were exactly the same five countries that they identify as the fastest movers (South Korea is effectively an island too), and then found their average death rate was much less than the other OECD countries, and would then presumably have attributed this to them being islands.  So, their paper would then have been entitled “Being an Island Creates Best Outcomes for Health, the Economy and Civil Liberties.”  Neither of these two approaches would be satisfactory.  Since death rates may be driven by many variables, a multivariate analysis is essential.  In my own analysis I used multiple regression, and found the following variables to be statistically significant in explaining death rates for countries: population density (low is good), population (low is good), whether it is an island (good), and the date of its first covid death (later is better, to provide more time for preparation).  I also found that the last variable was very closely correlated with how quickly a government acted, measured by the time interval between a country reaching 54% on the Oxford Stringency Index for government restrictions and the date of its first death (high values are best). See pp. 4-8 of:

https://www.medrxiv.org/content/10.1101/2021.07.15.21260606v1

  1. Conclusions from statistical analysis require tests for statistical significance.  The authors do not perform any such tests.  This is particularly unsatisfactory in respect of their graph of GDP outcomes for their two sets of countries, which are very similar.  Had they conducted statistical tests, they might have found that economic outcomes were statistically indistinguishable between the two groups, and therefore avoided making the claim that a particular type of government policy produced the “best outcomes for the economy”.
  2. The analysis in their paper uses classification data on government policy (countries are classified as fast movers or not) rather than numerical data.  The latter is more powerful if it can be done, because it avoids the somewhat arbitrary dividing line between the two groups and uses inter-group variation as well as variation between the groups. Furthermore, it could be done in this case.  For example, in my analysis, I quantified the speed of government actions by the time interval from reaching 54% on the Oxford Stringency Index until the first covid death.  It may be that the authors used classification data because their assessment of government policy was subjective.  If so, then there is the further problem that they may have been subconsciously biased towards judging these five countries to be the fastest movers because they already knew that they had the lowest death rates in the OECD data set. Such subconscious bias risks turning their analysis into advocacy rather than scientific analysis.  In addition, using classification data requires them to choose the dividing line between the two groups of countries, and this too exposes them to subconscious bias in choosing to include only five countries in the elimination group.
  3. Any analysis on whether government policy has favourable effects on covid death rates is exposed to the problem of reverse causality, i.e., government decisions may have been driven by observation of the death rate as well as affecting the death rate. This should have been tested for. The authors do not conduct any such tests.  By contrast, I conduct such tests in the Appendix to my paper.
  4. Drawing conclusions about which government actions produce the best outcomes on the basis of a cross-country analysis, as the authors do, can at best only offer conclusions that are valid in general, i.e., they might be true for 60% of countries but not for the other 40%.  Since policy is made by individual countries, the conclusions would then be worthless to individual governments.  The better approach is to conduct a cost-benefit analysis for each individual country, as I have done in my paper (and in a parallel analysis for Australia).

In summary, the article is not measuring the thing it claims to be measuring, and the analysis fails to consider more than one explanatory variable, and it presents no tests of statistical significance, and it uses classification data rather than numerical data, and it conducts no tests of reverse causality, and its results have no value for an individual government.

The paper should not then have been relied upon by the Skegg Committee.  In fact, it is hard to believe that the members of that Committee even read the paper; had they done so, they would surely have noticed that three of the five countries claimed to be following an elimination strategy did not even lock down.  Had they noticed that, and then contacted the authors of the paper for an explanation, and received the explanation I did, it would then have been apparent that the article was not in fact assessing the merits of elimination but the merits of moving quickly.  Moving quickly is good, as the article finds (and I do too) but it does not imply that elimination is better than (say) not locking down and taking other mitigation measures to minimise deaths.  If your house is burning, it may not be clear what action you should take to fight the fire or mitigate the damage but it is obvious that any action you take should be taken quickly.  Likewise the sun rises in the east.

The Skegg Report contains one other piece of empirical evidence on outcomes to date.  In para 8, the report notes that the benefits of New Zealand’s approach can be illustrated by comparing it with Scotland, with much the same population but which experienced 10,000 deaths compared to our 26.  Cherry picking one country is advocacy, not scientific analysis.  Furthermore, if one is going to cherry pick Scotland, one would have to ask how Scotland would have fared had it followed exactly the same policy as New Zealand.  Unlike New Zealand, Scotland has a land border with a place (England) that followed a much less stringent approach than us, and England in turn is separated from the European continent by only 20 miles, with a tunnel connecting them.  With these natural disadvantages, it is unlikely that Scotland would have experienced 26 deaths had it followed exactly the same policy as New Zealand.  What then is the point of citing Scotland’s deaths, other than to suggest (wrongly) that our very low death rate was due entirely to policy and not also to geography?

 

Protocol for re-opening New Zealand society

24/08/2021

Introduction

18 months on from the world’s fearful response to the arrival of SARS-CoV-2, we provide an alternative to New Zealand’s elimination strategy to one of ‘living with covid-19’. We are now back in level four lockdown indefinitely with escalating PCR positive ‘cases’. We urgently need to reassess New Zealand’s elimination strategy and whether it makes sense given the new information.

The revised strategy takes account of five major developments over the period:

  • The infection is far less threatening than originally forecast by authorities, including New Zealand, when they proposed lockdowns and other restrictions. Data from the WHO, CDC and other peer-reviewed studies show the median infection fatality ratio (IFR) is ~0.23%, not the projected 3.6%. The condition is therefore more akin to pandemics in 1957 and 1967 than influenza in 1918. Asymptomatic individuals do not spread the infection, removing the key idea underpinning lockdowns. Long-term health effects (“long covid”) have not proven any different to or more prevalent that those experienced in the recovery period from existing circulating pathogens.
  • Questions still remain about the accuracy of the polymerase chain reaction (PCR) test used to diagnose ‘covid-19 cases’. The virus remains yet to be isolated, the sequence of the virus was generated in silico (stitched together from computer databases) and many people who test positive are asymptomatic. In addition, the clinical symptoms associated with covid-19 are not unique.
  • It is clear that the average age of death with covid-19 is about the same as our life expectancy (~82 years). Older people are much more likely to die of covid than younger ones.
  • Very rapid development of vaccines and dissemination of these in New Zealand. The vaccines show some evidence of reducing PCR positive cases, but not of prolonging overall survival or reducing transmission. In many countries now with highly vaccinated populations, there are increasing numbers of breakthrough cases. It is now obvious that vaccines will not stop the spread of the condition long term. In addition, clear evidence shows a major increase in post-vaccination deaths and serious injuries.
  • Early treatment protocols are showing promise in the early treatment of cases otherwise destined to be hospitalised.
  • New Zealand’s very low incidence of covid-19, with the apparent absence of community transmission for many months, whereas covid-19 cases occur freely throughout the rest of the world. Now, we are faced with yet another lockdown and an increase in case numbers.

The vaunted elimination objective makes re-engagement impossible without an improved vaccine administered as often as necessary to most of the population.

New Zealand cannot sustain economically or socially the years of border closure, threat of lockdowns, social disruption and government debt, needed to reach this position, if it can be reached at all. We believe, frankly, this to be a utopian pipe dream, but necessitating dystopian government dictates. The fabric of our society will be rent – then restitched to what?

We propose an approach that slowly and carefully manages our entry back into a world where covid-19 exists, and where it can exist in New Zealand without causing unacceptable harm.

Guiding Principles

The risks of mortality following covid-19 infection have been grossly exaggerated. As observed in other pandemics, a high degree of ascertainment bias has occurred that has further exaggerated the importance of this condition in the minds of scientists, decision makers and politicians. This has led to an over prioritisation of the illness above many other health issues. In turn, this exaggerated threat has led to mortality and morbidity from other diseases due to the imposition of lockdowns and disruption of usual medical care.

The economic effects of lockdowns and border closures, leading to unemployment and poverty will lead to further health deterioration that is out of proportion to the threat of covid-19. Consistent evidence also highlights that lockdowns do not limit the spread of infection.

Now, it is important to note that hospital treatment for covid-19 patients has improved considerably during the course of the pandemic and that hospital mortality has declined. Potential treatments are also available to reduce morbidity and mortality include the use of both the micronutrient vitamin D and anti-parasitic and anti-viral drug ivermectin. It is also clear that metabolic disease is an important contributor to death with covid-19, and it also raises risk of death from other diseases. Addressing dietary risks related to metabolic disease is also worthwhile to reduce potential harm from covid-19, such as reducing sugar intake.

These guidelines were inspired from those produced by the group who published pandata.org.

Ongoing pursuit of elimination is risky

New Zealand is the only country in the world now continuing to attempt to eliminate cases. Many countries that were attempting to eliminate covid-19 have now given up, such as Singapore, UK and Australia. It is a dead-end strategy which will leave New Zealand isolated and vulnerable, in a (possibly) covid-free bubble. Even if elimination is possible and the reward warrants the financial and social cost, cases will still exist throughout the rest of the world – endemic for the foreseeable future (hundreds of years). To keep it out, New Zealand will need to retain covid-19 border testing indefinitely. Similarly, lockdowns and tracing and testing have no time limit.

There are three ends to the elimination strategy:

  1. A cataclysmic failure at the border, such as the beginnings of which we are now seeing, or a winter-resurgence within the country, in which infection sweeps quickly through the population. Lockdowns would, like the US and UK, not protect us.
  2. The infection becomes endemic with low levels of circulation and winter peaks, like the varieties of influenza and coronaviruses that circulate. This is likely to take many years. New Zealand would need to decide a point at which it could open.
  3. Future vaccines may be developed to completely interrupt transmission of covid-19. The development of the currently available partially effective vaccines has been the quickest ever, and faster than we imagined. We do not yet have evidence that the current vaccines reduce viral transmission through a population. Given performance to date, this evidence might one day eventuate. But the rest of the world is not trying to eliminate covid-19 and appears satisfied with the imperfect protection of the current vaccines. That makes it uncertain whether there will be a commercial incentive to ever invent such a comprehensively protective vaccine, since the existing ones are not as effective as required to maintain population elimination.

Our belief is that none of these exits from the elimination strategy are palatable.

Instead, New Zealand should prepare for, and carefully manage, the inevitable introduction of covid-19 to New Zealand.

Frequently asked questions

Do new variants and strains (lineage B 1.1.7 or delta) pose an increased risk of harm?

Every virus is thought to have thousands of variants. There are over 100,000 alleged variants for covid-19. The fact that there are new strains is not important. What’s important is their effect. With the UK strain, the claim is it transmits easier. We haven’t yet seen any convincing evidence that new strains are more dangerous.

Has there been increased overall mortality as a result of covid-19?

Yes, there has been increased overall mortality in some countries, but not all. Many countries, such as Malaysia, Cyprus, Costa Rica, Uruguay, Japan, Singapore, Denmark, Finland, Ireland, Luxembourg and Malta have not. Excess death is also statistically associated with the period after lockdowns in between country comparisons and between US states. Since the average age of death is close to our life expectancy in almost every country, much of the excess mortality is likely to be related to displaced mortality, and light influenza seasons in recent years, leaving a high number of people who are frail and elderly. It is also clear that some of the excess mortality was due to responses to covid-19, such as abandoning non-invasive ventilation for intubation and mechanical ventilation and prematurely sending infectious patients from hospital to rest homes. Hospital mortality in New York has now dropped by 70% since the beginning of the pandemic.

Does evidence support the wearing of masks to prevent infection?

The best evidence from a randomised controlled trial, the Danish mask study, couldn’t find any evidence to support mask use, particularly cloth ones, to protect the wearer. That also indicates that they are not preventing transmission. And asymptomatic people are unlikely to transmit the infection anyway.

What is the extent of the economic recession?

Globally, the World Bank is saying we are now facing the greatest recession since World War 2, demand in food banks in New Zealand has doubled or trebled and we have now thrown more than 50,000 adults in New Zealand into the dole queue, since March, when lockdowns and border closures began.

The health effects from the widespread panic over covid-19 has also produced many mental problems. For example, there has been an increase in children hospitalised for eating disorders both here in Auckland and in Melbourne. In the UK, mental health scores have deteriorated.

Does asymptomatic spread occur?

A mass testing study in Wuhan, a city of 10 million residents, identified 300 asymptomatic cases, with no evidence of spread of infection from them.

Are you just scientific outliers?

We might seem a minority in New Zealand, but our approach is the same as the Great Barrington Declaration, a view on covid-19 signed internationally by 15,000 medical and public health scientists and almost 44,000 medical practitioners.  The counter viewpoint signed by supporters of lockdowns only mustered ~4,200 signatories.

The Plan

Brief guide
  1. Offer enhanced protection and treatment for covid-19 to vulnerable people.
  2. End mass testing, contact tracing, quarantine and lockdowns.
  3. Vaccination should be voluntary and with informed consent and transparency of both efficacy and safety data.
Healthcare recommendations
  1. Since approximately half of fatalities worldwide with covid-19 have occurred in people living in rest homes, this should be the focus of protection. Effort should be given to protecting those who are at high risk of fatality from covid-19, which are individuals aged greater than seventy-five years, particularly those living in supported residential care, and those with metabolic health conditions, such as diabetes, obesity and cardiovascular disease. Measures to protect these people could include regular testing of health workers with respiratory symptoms, who have a high level of exposure to vulnerable people. Strong exclusion policies for workers with respiratory symptoms are important. Ensure people with covid-19 are not in contact with vulnerable people during their infectious period. Other measures include:
    1. Minimise the number of nursing home staff a resident is exposed to.
    2. Provide outdoor areas for socialisation of rest home residents where transmission of the infection is likely to be lower.
    3. Enforce strict exclusion policies related to workers or visitors with any respiratory symptoms.
    4. Encourage supplementation of vitamin D and sun exposure for vulnerable people, since trial evidence supports the use of this micronutrient to prevent intensive care admission in hospitalized patients.
  2. End mass testing for the infection and contact tracing. The test should be only used within a clinical context of a characteristic clinical picture, compatible with a lower respiratory infection within hospitalised individuals.
  3. Increase capacity in hospitals and intensive care units to cope with seasonal demands of respiratory illnesses, including covid-19. As stated, early treatment on diagnosis promises to reduce admissions
  4. Cases should only include those who test PCR positive, at a limited cycle threshold value, with compatible symptoms of a respiratory infection.
  5. Deaths from covid-19 should include only those who fulfil the criteria of being an active covid-19 case temporally related to their death, with no other likely competing cause.
  6. Eliminate mask wearing in the community, since evidence does not support their use to prevent infection in the community.
  7. Vaccination should be entirely voluntary with informed consent of the risks and benefits as more information about their efficacy and side effects come to hand. Vaccination for children of school age should be withdrawn since they are not at appreciable risk of covid fatality. Dangers of exposure to the vaccine, particularly to pregnant women, should be made clear and Ministry of Health information updated accordingly. Vaccination passports or any form of discrimination based on vaccination status should be abandoned, since the vaccines do not convincingly reduce SARS-CoV-2 transmission.
  8. Consider the routine use of vitamin D and ivermectin in the treatment of hospitalised covid-19 infection.
Societal recommendations
  1. Abandon the use of either regional or national lockdowns to contain viral spread, since they are unnecessary, economically disastrous and ineffective.
  2. Schools, childcare centres and universities should not be subject to restrictions and face-to-face learning should have no restriction since children are at extremely low risk for covid fatality.
  3. End all restrictions on businesses.
  4. Undergo a phased re-introduction of normal travel across New Zealand’s border. At first, a risk-based approach may be undertaken, as shown in the following web app and accompanying paper, which has been published in the New Zealand Medical Journal. This strategy indicates a method for opening NZ’s border, based on the estimated prevalence of covid-19 infection in the country of the traveller’s origin. This would enable travellers to come from several countries immediately who have a very low prevalence of covid-19. New Zealand should then aim to end travel restrictions completely, should this initial strategy be successfully enacted. In support of such a stance, the European CDC, for example, has now recommended the dropping of covid-19 testing and quarantine across borders.
  5. End the covid-19 elimination strategy in New Zealand. With cases widespread globally, it is clear that such a strategy is neither sustainable nor beneficial from a perspective which considers both the costs and benefits of such a strategy to New Zealand. Eventually, infection is likely to become endemic and part of the usual seasonal respiratory illnesses that affect New Zealanders every year.

Reflections on the Skegg report

By Dr Martin Lally

Director, Capital Financial Consultants Ltd

lallym@xtra.co.nz

The government has recently released a report from the Covid-19 Public Health Advisory Group chaired by Prof David Skegg (the “Group”), relating to future Covid-19 policy, and intended to answer various questions.

https://www.nzdoctor.co.nz/sites/default/files/2021-08/Embargoed%20Skegg%20advice.pdf

The first of these questions was: “Is an elimination strategy still viable as international travel resumes and/or are we going to need to accept a higher level of risk and more incidence of COVID in the community”?  Viability is a very low bar for any strategy to cross.  More important is whether continued use of the elimination strategy is optimal.  The Group recognised this deficiency in the question and proceeded to answer both questions.

In para 16, the Group concluded that continued recourse to elimination as international travel resumes is “the best option at this stage”.  In para 10, they defined elimination as “zero tolerance towards new cases”.  In para 15 they recognised that occasional large outbreaks may still occur, and proposed eliminating them by physical distancing, mask wearing, testing, contact tracing, and “localised elevations of alert levels”.  The latter words are a euphemism for lockdowns.  In para 5, they acknowledged that “no-one knows what the outcome of this pandemic will be in say 3-5 years’ time”, and that more dangerous covid variants may emerge.  Lockdowns may then be even more frequent and severe than they have been to date.

In describing elimination as the “best option at this stage”, the Group implies that there are at least two alternatives to it.  However, the only specific alternative mentioned by them involves ongoing “pronounced physical distancing, wearing masks in most indoor places, and separating high risk individuals from family and friends during winter months” (para 19).  This is an extreme alternative to an elimination strategy.  Governments do not in general adopt either of these extreme approaches to other contagious diseases, such as the flu, but instead adopt other approaches that impose no requirements upon the entire population.  Such an approach might be appropriate for covid, but the Group does not even contemplate that possibility, let alone analyse it.  Acting as if there is only one (extreme) alternative to one’s preferred policy when this is not the case is not analysis but marketing.

In support of its conclusion that continued recourse to elimination is optimal, the Group presented three arguments (in paras 17-21):

  1. Doing so ensures that “our health system is not overwhelmed by large numbers of patients requiring care.”
  2. Doing so will obviate the need for “pronounced physical distancing, wearing masks in most indoor places, and separating high risk individuals from family and friends during winter months”.
  3. Doing so preserves the option to later switch to the alternative strategy.

No disadvantages of the elimination strategy were mentioned.  This cannot be because the Group believes there are none because it acknowledges their existence in its para 21, where it refers to the possibility that “the costs of elimination outweighed the benefits”.  The Group does not identify these costs, but they include the GDP losses from lockdowns, the behavioural problems emanating from the attendant unemployment, and disruption to the education of students, and the Group accepts that future lockdowns are possible under an elimination strategy.  As with acting as if there is only one (extreme) alternative to elimination, listing its advantages but not its disadvantages is marketing rather than analysis.

The normal practice in assessing health interventions in this country and elsewhere is to estimate the Quality Adjusted Life Years (QALYs) saved by an intervention net of its costs, and to favour it only if this difference is positive.  The Group carries out no such analysis.  It cannot be unaware of this standard practice, because every member is an expert in health policy (most at Otago University), and the University runs a program (BODE3) to identify the health interventions that satisfy this QALY test:  https://league-table.shinyapps.io/bode3/

Furthermore, in respect of point 1, there is a clear implication that our health system is not currently overwhelmed.  The contrary is true, and manifested in long queues for many operations, with some patients dying from the ailment in question (or another one) before they reach the head of the queue.  Moreover, even if our health system sans covid were able to accommodate all demands on it, the emotive verb “overwhelmed” would cover every excess demand scenario down to only a handful of covid patient not being catered for.  An analysis should estimate the extent to which the system would be “overwhelmed”, and the deaths that would result from that.  An emotive verb is not a substitute for analysis.

Point 1 also implies that the capacity of our health system is an immutable feature of nature.  However, its capacity can be increased, and should have been in response to the pandemic because the benefits of capacity increases (in the form of lives saved and/or lockdowns avoided or mitigated) dwarf the costs up to some point.  Lack of time is not a viable excuse.  The Chinese built a hospital in a week, and even the UK managed in the course of a few weeks to convert several existing buildings into hospitals with the capacity for thousands of patients (“Nightingale” hospitals).  Our response over the 18 months since the pandemic arrived has been virtually imperceptible.

Finally, in respect of point 3, the Group states in its para 21 that “if it became clear over the next few years that the costs of elimination outweighed the benefits, it would be a simple matter to follow the example of other countries.”  However, the Group’s report consisted only of listing the advantages of elimination, ignoring the disadvantages, and then declaring elimination to be the winner. The Group then favours something being done in the future by somebody else (in the form of recognising the costs of elimination and comparing them to its benefits) that it entirely fails to perform itself.

Zero Covid is not a necessary or sustainable solution for New Zealand

Simon Thornley

6/7/2021

We have recently been told that “Life’s not going to go back to 2019 any time soon.” and that we need at least 83% of us vaccinated for measures such as lockdowns and quarantines to be a thing of the past. Other experts said these estimates were “plausible”. In fact, the figure might be as high as 97%. Before we abandon any dream of returning to normal, let us consider the broader issue of how much certainty we can place in these pronouncements, and whether we should now be putting our skeptical spectacles on.

These days it is easy to live under the illusion that specialists in any field have it all together. The other day my oven started burning food that I thought was put in to keep warm. I assumed the thermostat was broken, I ordered and installed another, but the problem persisted. I couldn’t work out what was wrong. I finally gave up and called a very good appliance repairer, who within ten minutes had found the short and the oven now works almost as good as new. The same generally happens when I bring my car in for a service. Whatever wasn’t working, now is and the problem is solved. Even I can now repair a computer that gives me the blue screen of death and fails to boot. The Windows recovery USB is a beautiful thing and is worth looking-up if you haven’t discovered it yet.

All of this creates the false impression that we live in a world of certainty and that experts can solve any problem. This assumption is safe when it comes to human designed machines and usually there is either an expert somewhere or a youtube™ video ready to give you advice about how to fix something that is broken. Such advice is often built on a profound and subtle understanding of how a machine normally works, how to distinguish normal from abnormal behaviour, and replace the faulty part in question.

The same is not true, however, for my chosen specialty. Epidemiology is fraught with uncertainty as we often have competing information from different areas and we need to decide which evidence is most important and most reliable. About covid, for example, we have seen this in action. We are still told to wear masks on public transport in New Zealand. Mask proponents will use this observational study to justify their use to prevent infection, whereas people opposed to their use may point to trials such as this one. Now both parties have evidence to fall back on and justify their viewpoints. The question is then now “which evidence is superior?” Conventionally, trials, such as the DANMASK one is generally considered better evidence than observational ones, since all other differences, other than the one under study (masks or no masks) are cancelled out by design. Instead, observational studies cancel out other factors through statistical means, which are clunky and we can only account for what we know, whereas the trial rather miraculously accounts for what we don’t know.

This is all old news. Science writer Gary Taubes pointed to this many years ago in a seminal article, asking the question of whether epidemiology had faced its limits? Taubes made the relatively straightforward observation that studies purporting to answer the same question in epidemiology often came to diametrically opposed conclusions, so it was hard to know where the true answer lay. Examples in the recent past include the questioning of the belief that saturated fat is the cause of heart disease. This has been dogma for many years, and now the lack of statistical evidence in support of the hypothesis is starting to more than raise eyebrows. Sugar intake, traditionally thought to be healthy, is now considered a prime suspect, taking the place of the formerly guilty animal fat.

This should now give us pause for thought as the country is given no letup in the torrent of bad news that seems to stream from authority on the covid-19 path. Although, I acknowledge there are different views of covid-19 and those who think it is terrible will point to scenes of overwhelmed hospitals in India and other places, there are also many reasons to be optimistic. We now have much data about the fatality ratio of the virus, and it is now in the region of 0.15%, not far off seasonal influenza (0.1%). The fear created by the spread of the latest ‘delta variant’ shows a case-fatality of only 0.1% in UK data. This is even with systematic exaggeration of death reporting which we are now only just appreciating. Deaths rates from covid-19 have dropped precipitously in many hospitals.

In perhaps the most sinister twist, we have our medical council stating that we may only discuss  evidence-based information about the COVID-19 vaccine if it aligns with government issued information, implying that any other information is anti-vaccine and not acceptable. This is despite new information leading to 18 countries withdrawing the AstraZeneca vaccine in order to protect their populations. The assertion that we are being told the “Whole Truth” is starting to now feel rather hollow. The recent case-series of cases of myocarditis and the rapid increase in reports of post-vaccine death in the US demands a cautious approach.

Te Pūnaha Matatini’s latest headline grabbing piece is based on another complex model that paints us all in a corner until we are all vaccinated. Even children, who have almost zero risk from covid-19 are targeted for the jab. Reading the document, I can’t help but yawn. The underlying assumptions are that we have no background immunity, it is only achieved through either infection or vaccination. It is also clear that the only goal is to defeat covid-19. Nothing else matters. There is not one mention of vaccine adverse effects – these are of no interest on the road to zero covid. It is almost as if this group is living in a parallel universe where the only concern is defeating the virus. This group who gave us visions of mass death that prompted lockdowns does not discuss the issue of pre-existing immunity from other coronaviruses that provide protection to SARS-CoV-2. Other modelers are drawing attention to this as a major reason for exaggerated death estimates early in the covid-19 saga.

The importance of the defeating covid-19 must be balanced against the growing evidence of harm from the vaccine and from restrictive measures. It is almost as if reports of vaccine harm don’t exist to the mathematical modellers. Physicians calling for the withdrawal of the vaccine stating there is “more than enough evidence on the Yellow Card system [UK vaccine side effects reporting system] to declare the COVID-19 vaccines unsafe for use in humans” must be deluded. The rate of 1/50,000 covid-19 vaccinees dying and the 1/70 having adverse effects reported after the vaccine must simply be co-incidence. These admonitions   along with the recent finding of strong cross-reactive immunity to SARS-CoV-2 in children hasn’t seemed to have dampened the Ministry of Health’s enthusiasm to vaccinate this age group.

In a recent telephone call from Professor Michael Baker, I was told that the average number of years of life lost from covid-19 was sixteen. I asked him what the average age of death from covid-19 was in this country? He couldn’t tell me. He asked me what that I thought that figure was. I responded that it was similar to our life expectancy: about 82 years. The same is true overseas. The combination of an average of 16 years of life lost and average age of death from covid-19 logically means somehow the virus is targeting people who would have otherwise lived to 98 years. This seemed implausible to me. Professor Baker agreed with me, however, Nevertheless, one week later he made the same claims about average life years lost. During that lecture he dismissed everything I’d said during the covid-19 saga as “misinformation” and accused me of “cherry picking” data. I had the same conversation with a stuff.co.nz reporter about one week later. Whatever else covid-19 is doing, we should not simply assume it be prioritised above all other concerns. We need to face the vaccine and the virus with our eyes open. From these data, it is not overall reducing our life expectancy.

It is a positive sign that Singapore, UK, and now Australia have recently announced that they have abandoned ‘zero covid’ as unsustainable, in favour of living with the virus and eventually returning to normality, albeit with vaccination. We urgently need to remember that the pretense of ‘one source of truth’ is anti-scientific, and that good science demands freedom to raise and debate uncomfortable evidence.

Analysis of NZ serology study

In the year since New Zealand closed its border and adopted an ‘elimination strategy’ against SARS-Cov-2, only one reliable serology test has been conducted. During this period at least 47 serology studies have been conducted throughout the world. Serology tests were banned from import or sale in NZ.

The result of the authorised study of 9806 blood samples taken in December 2020, was pre-print published (not peer reviewed) on April 19: https://www.medrxiv.org/content/10.1101/2021.04.12.21255282v1

The headline result is that it found antibodies to SARS-CoV-2 in 0.1% of samples.

This is lower than we expected – especially when compared to the prevalence found in other nations of studies conducted earlier in the pandemic (as high as 50% in India). It is also much lower than the NZ prevalence of H1N1 (30% positive antibodies), which triggered health authorities to abandon elimination plans.

The title and commentary of the paper suggests this low level is explained by elimination of the virus. It is directly explained by the estimated 3-month half-life of antibodies (S and RBD, compared to month long half-life of N protein). Our reference paper on seropositivity is https://www.medrxiv.org/content/10.1101/2020.07.16.20155663v2.full.pdf. That means ‘fresh’ infections have been falling. This undoubtedly means that border closure has cut off supply of renewed infection but tells us very little about how much infection existed in NZ at the time of the border closure.

Even if you would like to believe the result shows the elimination strategy has throttled infection rates, you cannot ignore that it simultaneously proves that elimination is impossible. The 0.1% prevalence is double the number of identified positive tests. For every identified case, there is at least one other person with covid-19 who has not been identified. That means there has been at least 5000 cases in NZ (5,000,000*0.001).

Worse still, community infection is higher than thought. The study shows the ratio of previously detected locally acquired cases to known cases is 6:8. The number of locally acquired cases from the Ministry of Health is 2600 – 865 in MIQ = 1,735. This indicates that there were 2313 (1,735*8/6) extra locally acquired cases that were not detected.

If we wanted to ascertain true cumulative exposure to infection, then 0.1% is certainly an underestimate, compared to influenza antibodies. The study makes no mention of the possibility of infection that can be found in T-cell levels e.g. from Karolinska. Those studies suggest that if the true infection rate could be, conservatively, 1.5 times the antibody prevalence.

We note that the eight undetected cases claimed in media coverage were widely geographically distributed, so could not have been from a localised cluster. Covid-19 was evidently widespread across NZ, breaking the fiction of being contained by lockdowns and tracking into ‘clusters’.

A big implication of the study is that we now have a more definitive infection fatality ratio (IFR) for NZ of 0.5% (26/~5000). Only a month or two before this serology survey Rod Jackson and the NZ Herald refused to retract articles that told New Zealanders the IFR was at least double that (over 1%). We trust they will now delete those articles. Most other NZ experts have been more recently citing the CDC’s IFR of 0.65% – which is now clearly too high in NZ.

Our search for an accurate IFR now has a more certain starting point. We know that about one quarter of the NZ deaths were attributed to covid without evidence of a positive test. We also know that given the half-life of antibodies, the real infection level must be higher than 5000.  A conservative level would be about 10,000 infections. So NZ’s IFR could be as low as 0.2% (20/10,000). This figure is concordant with median estimates from summaries of serology studies.

In summary, the study reveals a lower antibody level than we expected. It’s a surprise that indicates a likely waning of fresh transmission. But it reveals that we have had at least one undetected case for each detected case. This means:(a) the virus is not as deadly as first thought as these cases were not diagnosed since they didn’t come to clinical attention and(b) it is a fiction that New Zealand has detected each and every case of covid-19 and so can declare the virus ‘eliminated’.

Fact-checking Covid vaccine experts

Simon Thornley

18/04/2021

1014 words

In a recent interview with Radio New Zealand, a vaccine expert claimed that the risk of blood clot was 165,000 times higher after having covid-19, compared to the risk after having the AstraZeneca jab. This claim illuminates several misunderstandings of the nature of the SARS-CoV-2 virus, the true nature of the side effects that are worrying health officials overseas and the influence of misleading claims on social media.

Even though New Zealand is currently using a different vaccine, the emergence of blood clot reactions to some covid-19 vaccines has worried those who have been saying the vaccines are safe and effective.

In response they have tried to do something they refused to do with SARS-CoV-2; provide people with realistic data about the small risk posed.

To make the vaccine-related blood clots seem comparatively small, Dr Helen Petousis-Harris recently claimed that the risk of covid-19 blood clots was high.

She said the risk of clot from the AstraZeneca vaccine is about 1/1,000,000 against risk of clotting from covid-19 which is 165,000/1,000,000.

The frequencies of 165,000/1,000,000 are hard to understand until we start wiping off a few confusing zeros and end up with 16.5/100 or 16.5%.

Dr Petousis-Harris claims that 1/6 people who have covid-19 infection have a clot; not just any clot, but the rare brain vein clot being experienced by covid-19 vaccine takers.

All Helen’s words are taken verbatim from numbers on an infographic image doing the rounds on social media.

The statistic of 1/6 people suffering rare clots after being infected with the covid-19 virus comes from a summary study of hospitalised patients which evaluated the risk of pulmonary embolus and deep vein thrombosis in patients hospitalised for covid-19. Over half the studies included in the summary were from patients in intensive care. Some studies screened all patients for clots. The average of all studies showed a weighted proportion of 16.5% for both deep vein (leg) and lung clots.

Despite widely held belief, over 95% of people who test positive for covid-19 do not need a hospital, so would not have appeared in the denominator of the 16.5% figure. A study from Iceland, one of the most tested nations on earth, showed that 5% of positive patients for covid-19 were hospitalised, and only 1% went to intensive care. This means that the 16.5% figure is a very skewed proportion of all patients with covid-19. Since only 1-5% of cases make it to intensive care or hospital, that 16.5% chance should be less than 1%.

We know also that many more people have caught the virus than the positive genetic (PCR) tests say, as shown by serological tests and other immune studies. T-cell tests show that even more have been exposed to the virus, compared to antibody studies. The incidence of blood clots following covid-19 infection is simply not known, but it must be at least an order of magnitude lower than presented by our vaccine expert. So now the claimed 16.5% chance of blood clots across the population is not even 1%; it is closer to 0.1%.

Now comes the worst part of this attempt to mislead people about the vaccine risk; we’re not even talking about the same type of blood clot.

The blood clots experienced by some vaccine takers is cerebral venous sinus thrombosis, a deadly and rare condition.

The blood clots that threaten about 0.1% of us who catch covid-19 is deep venous thrombosis, a comparatively common condition found across all manner of hospitalised patients. It is so common that in one autopsy case-series, 10% of deaths in hospital patients who had the post-mortem procedure were caused by venous thromboembolism.

The background rate of cerebral sinus thrombosis is estimated to be 1.32 per 100,000 person years.

In contrast, the background rate of deep venous thrombosis is estimated at 50/100,000 person years, about 38 times higher than for cerebral sinus clots. The risk of leg clots is very strongly age-related, with older people more affected.

A direct comparison of the rate of cerebral sinus thrombosis in covid-19 patients compared to those who have had covid-19 vaccines has been carried out. The rate of cerebral venous thrombosis was higher in the covid-19 group compared to the vaccinated, but by a factor of 6 rather than 165,000-fold higher, as claimed in the Radio NZ interview. The cerebral sinus thrombosis group after covid-19 was more likely to have heart disease than those who had had the virus without the clot. The covid-19 group only counted PCR positive individuals, which as mentioned, underestimates the spread of the virus. The rate of venous thrombosis in the vaccinated groups (both Pfizer and AstraZeneca) was about 4-5 per million people in the two weeks following the vaccine. The risk of the vaccine is clearly higher than baseline which is an annual statistic, even if it is lower than for people who have had covid-19.

The administrative bodies of several nations are rightly concerned about the incidence of a rare type of blood clot from the AstraZeneca vaccine. Concern is justified when one particular risk of taking the vaccine is higher or worse than the risk of not taking it.

The image carrying the numbers quoted by Dr Petousis-Harris has been shared over social media by New Zealand doctors. I am sure they were well-intentioned, but it is never justified to allay fears using false information. It is always wrong to misinform people, particularly over the risk to their health of a medical intervention.

I am severely disappointed that our national broadcaster has not questioned these statements. It concerns a vaccine New Zealand is not using. But what happens when it does? What happens if rare reactions and deaths are attributed to treatments used here? We must be able to count on our media, and taxpayer funded experts to look at data impartially.

The conversation they held with Dr Petousis-Harris revealed a hopelessly exaggerated view of the severity of covid-19 in the minds of our “experts”, doctors, and the governing elite.

I call on Dr Petousis-Harris and Radio NZ to check the numbers, issue a retraction and an apology.

 

Injecting evidence into the vaccine spin

Simon Thornley, Gerhard Sundborn.

12 April 2021

We are usually supporters of vaccines, and our children are all immunised.

Yet we have deep unease that the least tested vaccine in living memory, for a virus posing little risk to most people, has been purchased at great cost, and is being commended to New Zealanders as “safe and effective”.

When Covid Plan B opposed the elimination strategy a year ago, it was not because of doubts over vaccines. We said the strategy was too costly to pursue while waiting for a vaccine. We said that most solutions were likely to be unwarranted by the small danger posed by SARS-CoV-2.

The early development of vaccine-like products is a triumph of science.

Plan B had worried that vaccines would take years to pass the usual safety and effectiveness tests. We hadn’t counted on the panic being so strong that usual stages would be curtailed.

The speed, haste, and enthusiasm with which covid-19 vaccines have been thrust upon us has made us pause and examine the evidence.

New Zealand has purchased enough of the Pfizer mRNA vaccine for everyone in the country. Several other supply arrangements exist in case one falls through.

We do not know the cost of the vaccines, as it has been hidden from us. Sources overseas indicate the cost to governments of the Pfizer/BioNTech vaccine as US$19.50/dose – or NZ$27.63 at current exchange rates. So for 10 million doses, NZ may have paid NZ$276 million.

That doesn’t include the costs of distribution, cold-chain, quality control and administration of the jab.

Is this vaccine worth the cost? What is the evidence for the vaccine’s benefit and are there any potential downsides?

A primary factor in whether a vaccine is warranted for a particular disease in pre-covid times has rested on three principal factors. These are, among others:

  • Benefits for high-risk individuals compared to the whole population.
  • Healthcare system and societal costs incurred by vaccination programmes compared to treating disease.
  • Life years and quality adjusted life years gained because of vaccines.

The World Health Organization has released criteria which focus on clinical consequences, such as safety and efficacy, but also encompass other areas such as public health benefits such as the reduction of infection rate.

The document mentions the ‘preferred’ need for at least 70% vaccine efficacy, with consistent results in the elderly. 50% efficacy is considered minimal. The endpoint may be a combination of disease, severe disease, and or shedding or transmission. The document says 6 months of protection may be acceptable, but one year is preferable.

The WHO discussion of vaccine safety is vague. It says a ‘highly favourable benefit to risk profile’ is ideal, but the benefits outweighing the safety risks is ‘acceptable’.

A footnote mentions that the ‘potential for enhanced disease’ should be considered. Clearly, authors of the document are cognisant of the potential for antibody dependent enhancement, a phenomenon present for other viruses such as dengue, Zika, Ebola and other coronaviruses. This occurs when high antibody concentrations are initially effective against a pathogen, but waning immunity and lower concentrations paradoxically enhance the severity of infection.

The true cost of the epidemic is hard to pin down, and we’re yet to see a formal cost-benefit analysis of the effects of the vaccine, since the long-term effects of the product are unknown.

The main choice facing New Zealanders now is whether to be vaccinated with the Pfizer one, so we’ll focus on this. The main evidence relating to this vaccine is outlined in the New England Journal of Medicine. The trial randomly allocated ~40,000 participants, roughly half each into vaccinated and placebo groups and followed them for two months to see whether they developed covid-19 infection. The study excluded people under the age of 16, pregnant women and people with a history of either covid-19 or any immunocompromising condition. The primary outcome was defined by a positive PCR test, with at least one symptom of infection.

The headline results were 169/20,172 covid-19 events in the placebo group, compared to just 9/19,965 in the vaccine group, giving an efficacy of 94.6% after two months. The most reported side effects from the vaccine were transient, such as fatigue, headache, and muscle pain. The two-month trial did not address viral transmission nor long-term safety and effect.

The trial has come under scrutiny for unexplained incongruities. Further documentation has revealed that the rate of ‘suspected, but not confirmed’ covid-19 were similar between the two groups: with 1,594 cases in the vaccinated and 1,816 in the placebo.

There was also an imbalance in exclusions due to unexplained ‘protocol deviations’. In the vaccinated group 311 were excluded, compared to only 60 in the placebo. The chances of being excluded from the trial were therefore (311/21,720)/ (60/21,728) = 5.2 times higher in the vaccinated group, a ratio which is extremely unlikely to be due to chance (P < 0.001). This finding is buried in papers only made available to US regulators, rather than highlighted in the trial results. The selective exclusion of individuals in trials is an area commonly exploited by drug manufacturers to exaggerate claims. The best evidence conventionally comes from including all randomised subjects (‘intention-to-treat’), whether they deviate from the trial protocol or not. Requests for scrutiny of the trial data, to understand what factors lead to these exclusions, have been ignored.

Since the primary outcome of the trial is related to mild covid-19 events, we know little about whether the vaccine prevents deaths from the virus. Others have indicated that trials will not be sufficiently powered to detect differences in need for hospital treatment, let alone death from covid-19, since the number of subjects and resources required for such a trial would be prohibitive. We cannot assume that prevention of infection translates to fewer deaths. For influenza vaccinations, for example, even though they reduce infection, that has not translated into lower mortality after widespread uptake.

The vaccine has been studied in a healthy population who are largely unaffected by covid-19 hospitalisation or death, even with subjects drawn from supposedly ‘hard-hit’ regions, including the US, Brazil, South Africa, Germany, and Turkey. This trial evidence supports reductions in mild covid-19 infections only. We simply don’t know whether the vaccine will prevent what really matters: hospital and intensive care admissions and deaths.

The trial confirms that for people of working age, the risk of fatality from covid-19 is extremely low. So low in fact, that there will be too few deaths to run a trial without spending an extraordinary amount of money on a very large one. The conclusion by health authorities not to run a trial on vaccine effectiveness to prevent death means they themselves conclude that the fatality risk of the virus, and hence need for a vaccine, is overblown.

New Zealanders are being offered a covid-19 shot with the inaccurate assurance that it is “safe and effective”. From the evidence reviewed here, this message is disingenuous.

The long-term benefits and harms from covid-19 vaccines are unknown since they have only been recently used in humans. This is acknowledged in Medsafe’s 58 conditions for the emergency use. They require early alerts to company reports about the product’s safety and possible benefits. If the government’s own officials are sceptical and demand transparency, we should as well.

A NZ doctor speaks out against Covid policies

We should be concerned

6 April 2021

By anonymous. 

Like many gravitating to the Covid Plan B webpage, I am increasingly concerned about our government’s and indeed the global approach to the management of the Covid-19 pandemic. There are so many aspects of the present situation that seem so completely surreal.

From the philosophical perspective, I am deeply concerned about the adulteration of the scientific method. Am tired of hearing the media admonish us to trust the science and trust the experts. I constantly need to remind those around me that science is a tool, a method which if correctly applied will answer questions in a meaningful way bringing us progressively closer to an approximation of truth. It is primarily a process of observation and to make our observations meaningful these must be conducted in a carefully controlled manner.

By contrast, the force dominating our present world view is a deceitful yet carefully contrived facsimile of science. It uses all the vestiges, regalia and language of science without meeting the fundamental criteria. The policies and interventions which are being foisted upon us in the name of this pandemic are based not upon controlled observation, but rather upon narratives, rhetoric and data derived from some rather dubious uses of modelling. To make the distinction I will refer to this alternative paradigm of polemics and extrapolation as scientism. It is a sleight of hand, a wolf in sheep’s clothing, the proverbial cuckoo in the nest of the scientific method.

Examples of scientific fraud that have been perpetuated on our populous over the course of the present pandemic are sadly numerous. But I wish to focus here on the novel reversible gene therapy which is being deployed to our New Zealand population under the auspices of the disarming banner of the term “vaccine”. Vaccines are central to our medical approach to the prevention of severe human disease. However, the present technology has never been used for this application on prior occasions. It is disingenuous to include this technology within the trusted envelope of the term “vaccine” without evidence that it is both safe and effective for use in this capacity. The suggestion that an individual’s access to employment, ability to access services and ability to travel could depend upon their participation in this uncontrolled human experiment should be deeply alarming to anyone who places any value on human rights.

I have deep concerns about the speed at which these experimental “vaccines” are being presented as the only solution to the pandemic. No one has been able to answer the question as to how we can be confident that the recurring problem of antibody dependent enhancement which plagued our prior attempts to produce vaccines to other coronavirus variants in animal studies has been overcome. The main safety concern may not lie in the deployment of these “vaccines” but rather in the exuberance of the inflammatory response which follows the subsequent exposure of a patient to covid-19 or a future coronavirus variant.

Science aside, I am alarmed at the campaign of propaganda directed at the public through our mainstream media. The media’s phrasing of Covid-19 is hyperbole at best or worse – blatant fear mongering. By prefixing reports with phrase selection “the deadly virus” it is little wonder that many of our fellow New Zealanders are living in the state of fear that paralyses rational decision making. I am unaccustomed to living in an environment in which rational discussion has become verboten. Never have I seen anybody who dares to ask legitimate questions, shutdown so vehemently and labelled “controversial” or a “conspiracy theorist”.

It seems quite clear that we are only “allowed” to conform to the narrative being presented to us by our government and our trusted mainstream media. We once lived in a free society, with free speech and open dialogue, this no longer seems to be the case. Should we be concerned? I am.

The author: I do not wish to disclose my identity, at least for the time-being. I have undertaken a protracted tertiary education which includes degrees in science (cellular and molecular biology and biochemistry) medicine and dentistry and a doctoral degree with research in molecular biology. I am lucky to be a member of the fortunate educated.

Govt policies must catch up with latest data on Covid19

Simon Thornley, Ananish Chaudhuri

1258 words.

António Egas Moniz was awarded the Nobel Prize in 1949 for frontal lobotomy, a supposed cure for mental illness. Ultimately, however, Moniz and the Nobel committee were wrong. The operation did irreparable harm to over fifty thousand patients and the results were far from the claimed ‘cure’.

Early in New Zealand’s Covid-19 story we were admonished with predictions of  80,000 covid-19 deaths by Professor Sean Hendy and his colleagues, even with stringent lockdowns in place. Recently, Professor John Gibson questioned the accuracy of these predictions as implausible because they would require our population to be almost 10-times larger, to square with the infection-fatality proportion reported by the WHO for countries like us. Yet Hendy doubled down on the predictions. Considering that New Zealand now has 26 official Covid-19 deaths, it seems at face value that Gibson is right. Hendy overshot the mark. By a lot.

What is remarkable now is the lack of insight into why these predictions were wrong. We have now learned so much more about Covid-19, we must update our ideas. The government’s own advice to its new Minister shows that Hendy’s exaggerated prediction will have enormous costs to New Zealand society. Crown debt is forecast to grow by 2.5 times to a level of NZ$200 billion in 2024, and the real value of output in 2020 is over five percent smaller than what had been forecast in 2019.

With so much at stake, it is essential that we take stock of what we have learned and why Hendy and his colleagues erred. After all, science is little more than the recalibration of our beliefs and predictions to match the stark reality of collected data. From what Hendy indicated in his response with revised predictions of 10,000 deaths he has learned little about the virus since the early forecasts. His response centred on explanations such as: vaccines arriving early, a modest change in the infection fatality rate (0.9% is the new value, compared to 1.0%), and the lack of capacity in intensive care.

What is most remarkable about these explanations is that none of them could possibly explain the discrepancy between Hendy’s original model and the observed deaths. Since the deaths are simply a proportion of the overall cases (infection fatality ratio), a 10% change can in no way explain the difference between models and reality, which differ by three orders of magnitude (3,076 times).

So, what have we learned about Covid-19 and why were Hendy’s models wrong? First, the models assumed the virus was totally new and that the entire New Zealand population was susceptible. Many studies now show that cross-reactivity and T cell responses to other coronaviruses protect us from Covid-19. Many of us will simply shake off the virus since our immune systems have already seen similar ones.

Hendy takes it as a given that Covid-19 is ten times more deadly than influenza, with no evidence cited. Calculating the ‘deadliness’ of a virus is a difficult issue, since it is dependent on accurately estimating cumulative numbers of infection – the denominator, as well as Covid-19 deaths – the numerator. Deaths are sensitive to definitions of what exactly constitutes a Covid-19 death, particularly in the frail elderly, who often have a range of other diseases.

To illustrate, Singapore has a strict definition of Covid-19 deaths, which requires a positive test and respiratory infection leading to death. The city state has registered only 30 deaths out of 60,019 cases (case fatality ratio: 0.05%). In contrast the UK, which has a comparatively loose definition, including all who died within a period of testing positive, has a case fatality ratio of 2.9%, 40 times higher than Singapore, from the same virus. The most comprehensive survey of infection fatality ratios, which account for positive serology, has yielded a corrected median of 0.23%, well under Hendy’s estimate. This figure does not account for T cell responses to the virus, and takes death recording at face value.

Evidence from wastewater in Barcelona and retrospective analysis of blood samples from a lung cancer screening study in Italy suggests that SARS-Cov-2 was circulating in Italy before its supposed discovery in Wuhan in December 2019. What do we learn from this? Since there was no excess death at that time, it cannot therefore be assumed that excess death that accompanied lockdowns is a direct consequence of the virus. Many of us have likely seen the virus and not known it, since it was circulating well before Wuhan, and health systems coped at that time.

It is remarkable also that Hendy’s doomsday predictions showed little appreciation of the age of deaths with Covid-19. Other authors predicted the magnitude of deaths in NZ from Covid-19 to those from World War 1, which averaged in the 20s of the soldiers who died. Spanish flu victims, similarly, had a median age of death in the twenties, but not those from Covid-19. The average age of deaths with Covid-19 are about the same as the life expectancy of that country. This means that the virus is certainly not as deadly as Hendy claims, since deaths from the virus will not lower the life expectancy of a population. Put another way, risk of death from the virus is no different to the background risks we face every day.

Hendy also fails to discuss the exaggeration in coding of Covid-19 deaths that has occurred during the pandemic. The fact that many deaths have been due to other illnesses and the usual process of recording death has been overturned. This panic induced exaggeration has also been a feature of many other historical epidemics of respiratory illnesses.

Another feature of the Covid-19 story is that much of the early high fatality was related to foregone opportunities for healthcare for other conditions. In the UK, emergency department visits halved during lockdown. To compound this, early mechanical ventilation in intensive care, which overloaded these units, inflated mortality from the virus. Statistical evidence now supports this policy as a cause of excess deaths in Covid-19 cases.

Hendy’s revised estimate that we must have saved at least 10,000 lives assumes lockdowns are effective. This is counter to the weight of statistical evidence on the subject. A between-country analysis showed no evidence that lockdowns save lives, either measured as a stringency index or from google mobility data.

We urgently need to return to the foundations of science which means a sober assessment of reality over failed forecasts. It seems Hendy is unlikely to champion such a cause, since his predictions have cost New Zealanders dearly. Wrong predictions are a routine part of science, but a stubborn adherence to them indicate a deviation from usual practise.

Our usual way of life, our ability to engage with the world, and much of our economy have been surrendered to erroneous predictions. Even with orders of magnitude differences from the reality of observed data, the author remains wedded to them.

The words of Nobel prize winner, Professor Richard Feynman are relevant:

“It doesn’t matter how beautiful your theory is, it doesn’t matter how smart you are. If it doesn’t agree with experiment, it’s wrong.”

Given what is at stake for New Zealand’s future, the last thing we now need is to cling to failed models. Rather, we must confront the frightening fact that much of what we initially thought we knew about Covid-19 was wrong. Dire predictions simply did not eventuate. The spectre of further lockdowns and strict border closures urgently need to be re-evaluated in this light. Feynman again:

“Reality must take precedence over public relations, for nature cannot be fooled.”

The surprising story of how ventilation killed covid19 patients in intensive care.

Simon Thornley

16/03/2021

Over a year now into New Zealand’s covid-19 saga, what can we learn from the experience of intensive care units? In the early days, protection of intensive care units and the scarcity of ventilators was a major factor shaping covid-19 policy.

New Zealand students were busy building ventilators, intensive care capacity was a major government concern, and became a key component of the elimination strategy.

The thought, early on, was that covid-19 was a completely new disease and that early mechanical ventilation was necessary in a patient’s treatment to give them a good chance to make it through. Since mechanical ventilation is a medical treatment, it must make things better, acting like a kind of super bellows, taking over when the patient ran out of steam, buying them time as their body beat back the virus.

The reality of intensive care experience has been somewhat different. It is well known that ventilators inflate the lung in an unnatural way, causing ventilator induced lung injury. They are far from a benign intervention and must only be applied sparingly.

Unfortunately, a certain level of jargon is necessary to dive deep into the ventilator story. A crucial measure of lung disease that is important in deciding to ventilate a sick or deteriorating patient is the ability of the lungs to soak up oxygen, known as the Pa02:FiO2 ratio. This is the ratio of oxygen pressure, measured from a patient’s artery relative to the percentage of oxygen being delivered, usually via a mask. This ratio indicates the ability of a patient’s lung to deliver essential oxygen to the body. Usually, values of 150 mmHg to 200 mmHg indicate the need for a ventilator. Early opinions from Wuhan, from Chinese anaesthetists, recommended early intubation, with patients having values as low as 300mmHg indicating need for a tube. In some hospitals, the milder form of breathing support, non-invasive ventilation, was not used due to the fear of spreading the virus to staff. In other areas, such as the US, financial incentives to ventilate were operating.

Early mechanical ventilation has been a spectacular failure, with the best evidence now showing that it did more harm than good. A recent study, published in January 2021, now has the wash-up from experience with 10,362 patients who have had covid-19 in the UK and been in through a critical care unit. These are covid-19 patients at the severe end. Almost 38% (3,933/10,362) of subjects died. The critical comparison was between those who were ventilated and those who were not. For those who were ventilated early, at low severity of lung disease (Pa02:FiO2 = 300mmHg), they had almost twice the rate of death, compared to those who weren’t, after accounting for all other factors. In fact, the most surprising finding was that for any level of lung impairment, those who were ventilated were more likely to die than those who were not. A conservative estimate of the importance of this finding, indicates that it accounted for about 15% or 1/7 of all the study deaths.

Naysayers may point out that the study was an observational one – not a trial – and that the results may be explained by doctors spotting unrecorded adverse factors that led them to put tubes down patients’ throats. An interview with North American intensive care doctors, however, contradicts this interpretation. Doctors spoke of asking patients to get off their mobile phones so they could put them on a ventilator. This was unusual practice, created by the fear of a new disease with an unpredictable course. Ultimately, it was learning to do less, rather than more which reduced mortality rates.

This created a sort of medical self-fulfilling prophecy of a deadly virus. The simplistic fixation on ventilators and the perceived need for them led to excessive use and premature deaths. Together with exaggeration of recording of covid-19 deaths, a vicious circle of fear took hold. The finding that Italy had ~10% of participants in a screening study of several regions of the country with antibodies for SARS-CoV-2 in September 2019, with no excess mortality at the time, strongly indicates that the healthcare and societal response, including lockdowns, were deadlier than the virus ever was.