Select Committee presentation Sept 2021

Evidence of Simon Thornley, to New Zealand Parliamentary Select Committee, on the Public Health Amendment Bill. September 2021.

The covid-19 response as exaggerated and profoundly harmful. Instead of mandating experimental vaccines and ongoing lockdowns, our group advocates for returning to protection of the elderly, increased capacity in hospitals and early treatment of covid-19.

There will be legal experts who will address the mechanics of the bill, however,  our focus will be on the scientific evidence that relates to the need for extended far reaching powers entailed in the proposed amendments to the Act.

I wish to draw your attention to epidemiological evidence that the threat of covid-19 is exaggerated in the minds of the government and media. This is relevant to the nature of the proposed far reaching powers. One such example is that the distribution of age at death with covid-19 is almost identical to the distribution of age at death in earlier years when the virus was absent.

Professor John Ioannidis, one of the world’s most eminent epidemiologists wrote:

“Median age of death with COVID-19 typically tracks average life expectancy in high-income countries.”

Many people are not aware that the average age of death with covid is about the same as our life expectancy – about 82 years. This information contradicts  that which  is often portrayed in the media, and by other academics that the average number of years of life lost from Covid-19 is 16. It is simply implausible that this is true, since Covid-19 would then be causing the demise of patients who would have otherwise lived to the age of 98.

One of the reasons that covid-19 has become exaggerated in the minds of the public, politicians and scientists is that the definition of a covid-19 death is loose. Yet such deaths are paraded in the media as tragedies due to the virus. From an OIA request in June, it was found that even a positive PCR test was not required to count as a death from covid. The definition in New Zealand or overseas do not indicate that the person would have otherwise survived were they not infected with the virus.

Other reasons to suppose the pandemic is severe is that there is excess mortality in some countries. However, closer inspection of this data shows that this excess death occurs in close proximity to restrictions in mobility of citizens in that country. This indicates that it is the response to covid, rather than the virus itself that is the primary problem. Other evidence points to the excessive use of invasive ventilation and restriction in access to usual healthcare that were the primary drivers of this excess death.

The PCR test itself has faced intensive scrutiny and has been not recommended for widespread use in the community. The diagnostic accuracy, which has been tested in a large German study indicates that the assay does not reliably even distinguish between people with or without symptoms of a chest infection.

What is more, evidence indicates that the restrictive actions of the government so far have already caused substantial harm. This includes at least a 50% increase in children attempting suicide and presenting to hospital. Unemployment has increased since March 2020 in New Zealand with a 30% increase in eligible adults requiring the jobseeker benefit over the period inwhich covid restrictions have been imposed. Special needs grants also spike over lockdown periods, indicating that these policies come down most severely on our poor communities. Severe lockdowns have cost the country at least $1B/week, a figure that is well outside the amount usually thought to be reasonable for such health spending.

In summary, our objection to the amendments in the act are related to the proposed legislation of disproportionate powers to contain a health threat that we believe has been grossly exaggerated. The powers contained within the act infringe many of our fundamental freedoms and rights and are now causing severe harm to the economy and health of our children. Our group wishes to advise the government that this act should be repealed rather than extended. Thank you to the committee again for the opportunity to present.


Vaccine mandates twist Covid-19 saga


The most recent twist in the covid-19 saga is forcing hard-working New Zealanders to believe in the story of the ‘deadly virus’ and ‘saviour’ vaccine. This will inevitably mean many will now be forced to choose between their jobs and their sense of autonomy over their own body and health. The death of the elimination strategy has meant that the accelerator has been applied to the vaccine pedal. Hang on a minute, where is the evidence to back this up such a policy?

Most recently, leading scientists advising the government have put their irrationality on show. They argue that we simply cannot live with endemic covid-19 and that we will all get SARS-CoV-2 under the reign of delta. The march to stamp out the virus “must” continue as there is no other way. Professor Rod Jackson has stated “”I’m freaking out in a major way Auckland, we just have to suppress it until we all get vaccinatedI mean we need everyone vaccinated before December, and if we got 95 per cent of the population vaccinated by [then]… yeah, then you can have a holiday.

According to Professor Jackson, the virus is extremely deadly and the only way out is vaccination and mandates which are all logical responses to the threat. First teachers, then doctors, nurses, and everyone else with a chance of spreading the virus. Where will it end? One could be forgiven for advocating such a strategy if we hadn’t been able to observe what is happening in other countries. But we have:  the experience of Israel, Iceland and others show the virus will continue despite vaccination. Singapore is the most extreme example, now with 85% vaccination, yet their covid-19 cases are higher than ever. Vaccines are clearly not the end of covid-19 and mandates will not change this.

A recent between-country epidemiological study has confirmed this. The epidemiologists found no relationship between the percentage of population fully vaccinated and new COVID-19 cases in the last 7 days. Counter-intuitively, the trend suggests that countries with higher percentage of population fully vaccinated have higher COVID-19 cases per 1 million people.

Politicians and most of the public are clinging to the hope of vaccinations. I conclude it is based entirely on unsubstantiated fear. Despite all evidence to the contrary, the idea that Covid-19 is deadly has taken even stronger hold. No questioning of this is allowed. The protagonists argue that on average sixteen years of life are lost from the virus.

A couple of pieces of information sum up the lack of real threat from Covid.

  1. Covid-19 deaths in New Zealand occur at about the same age (red line) as background (black line: figure 1). In fact, the two age distributions are statistically indistinguishable (P = 0.998). This could be a freak of the low covid-19 numbers in New Zealand, except that it is found again in almost every other country you care to look, no matter how many cases they’ve had. A German researcher found a very similar pattern in a country with 4.3 million cases and 94,000 deaths. It is very difficult, even, impossible to reconcile the 16 years of life lost per covid-19 death with age-at-death comparison. Doing so would mean that covid-19 is selectively targeting people who would otherwise live to the age of 98 years. This is simply implausible. It is hard to see how scientists could be so pessimistic, when the data on covid-19 deaths are shouting for optimism.

Figure 1. Background death in New Zealand 2019 to September (black) and national covid-19 deaths March to September 2020.

  1. No one is discussing is the downsides of the vaccine. In the following figure (not made by an official source) we see a summary of the highest level of evidence known about the Pfizer vaccine which is currently on offer in New Zealand. It summarizes the participants, covid-19 cases and overall deaths. I didn’t make this diagram, but I wish I had. When reading the Pfizer 6-month update, we see that 21 people died in the group vaccinated or eventually vaccinated, compared to 15 in the placebo group. This result does not fill me with confidence, even though the reduction in covid-19 cases was so dramatic in the vaccinated group compared to placebo.

Why do the excess fatalities in the treated group sap my confidence in the vaccine? Well, most of us who are thinking clearly, want to live longer, not just avoid Covid-19. This trial clearly signals that you are better off with the placebo if your objective is long life. The end-point of overall death is an important outcome in epidemiology, since it is easy to measure, and weighs both benefits of the intervention along with risks. Another author has tallied serious medical events in all covid-19 vaccine trials used in the United States, and all such analyses question vaccine use.

Figure 2. Study flow for the 6 month Pfizer trial follow-up.

Another concern is not being addressed is the 100-fold increase in reported deaths after covid-19 vaccine in the United States, indicating poorer safety than initially indicated in the trial. To support this interpretation, case-series of myocarditis, unusual clotting and haematological abnormalities have been reported in close proximity to having received the vaccine.

Children are at almost zero risk of death from covid-19 and so the risk-benefit in this group is severely questionable.

To sum up, when assessing the point of a vaccine, especially mandated ones, it is vital to;

  • Realistically appraise the threat, and the threat of Covid-19 is negligible.
  • Consider the overall benefit and harm associated with the vaccine, and even on Pfizer’s own trial results, the harm is at least equal to the benefit (deaths vs much reduced illness).

There is a heavy price for mandating vaccines. We put lives directly at risk from the medical intervention. We embed a culture of fear and intense community discord. We give up hard-won human rights and autonomy.

The time for slogans, gut reactions and freaking out is over. We are traveling a dangerous and hysterical path.

A sober look at facts is our only hope for a return to reasoned assessment of the best path forward. The Nordic countries are leading the way and are now abandoning almost all covid-19 restrictions. It can be done; it hasn’t led to catastrophe. We can live with the virus. All it takes is a little courage and clarity of thought.

Dissection of Prof Hendy model presented at Ardern conference 23/9/21

We do not hold this type of modelling in high regard.

First of all, it is myopically focused on reducing harm from Covid-19. It is hard to understand the utility of presenting such results without context.

There is no mention that the average age of death of those predicted to die will be about the same as our life expectancy. To put it slightly differently, most of those forecast 7,000 deaths were on average likely to die that year with or without SARS-CoV2. About 35,000 people die each year in New Zealand and half of them are over 80 years old.

There is not a single mention in any of the Matatini documents of deaths among Covid-vaccinated people. Even Pfizer’s latest trial shows more deaths in the vaccinated group compared to the unvaccinated.

It is misinformation to build a model that generates a result used to promote vaccination without mentioning that up to half of the predicted deaths will be among vaccinated people.

A quote from the study:

During the blinded, placebo-controlled period, 15 participants in the BNT162b2 group and 14 in the placebo group died; during the open-label period, 3 participants in the BNT162b2 group and 2 in the original placebo group who received BNT162b2 after unblinding died.

There is a very concerning issue in this Pfizer trial – that the vaccine itself might be responsible for some of the deaths in the trial, not Covid.  It is not very convincing that there was a 40% (20/14) increased overall death rate in the vaccinated and eventually vaccinated group compared to controls.  While the Pfizer paper asserts that the deaths in vaccinated people had nothing to with the vaccine, it does not provide evidence.

This is a consistent trend across all covid-19 vaccine studies

The predictions from the study that high vaccination uptake will result in reduced harm from covid-19 are not borne out by real world experience, such as from Israel:

It is clear that high levels of vaccination coverage have not lived up to the hope indicated from the results of the trials.

The Covid policy responses modeled in the work are conventional ones already proven ineffective over the past 18 months in other countries. The model does not attempt to work out results of using other strategies, some now being attempted in countries such as India.

For example, meta-analysis of trials (conventionally considered high level evidence) support the use of Ivermectin to reduce covid-19 mortality.

The use of models without comparing or contrasting with actual trials, amounts to misinformation. Trials are conventionally considered stronger evidence than modelling studies.

It is deeply worrying that the government is using models to justify responses, when we have actual evidence and trials from the past 18 months of experience in other countries. It feels disturbingly reminiscent of the now widely discredited models used by other Western Governments very early in the pandemic.

What Prof Hendy gets wrong


Dr Martin Lally

Director, Capital Financial Consultants Ltd

Professor Shaun Hendy is another prominent adviser to the New Zealand government on covid-19 issues.  Like Professor Baker, he combines frequent commentary via popular media in support of lockdowns with papers written (with numerous co-authors) in the academic style.  However, unlike Professor Baker, he does not seem to have done any prior research in epidemiology (he is a Professor of Physics).  His epidemiological work starts with his first covid paper, which was posted to a website on 25 March 2020:

Table 2 of the paper presents predictions of the death tolls in New Zealand from a range of possible control strategies.  No control yields predicted deaths of 83,000 (1.67% of the population).  Case isolation and quarantining of members of their households reduces this to 62,500 (1.25% of the population).  Adding population-wide social distancing reduces this to 3,000 (0.06% of the population), and adding school and university closures reduces it further to 20.  On page 7, they consider a strategy they describe as “mitigation”, with a predicted death toll of 25,000 (0.508% of the population), and involving a combination of periods of low control (case isolation plus household quarantining) with periods of high control (add population-wide social distancing and school and university closures) as required to keep the number of cases within the capacity of the hospital system.  None of these strategies correspond to mitigation as defined in the 23 March published paper by Professors Baker, Wilson and Blakely (isolation of the over 60s). The most interesting features of the Hendy paper are:

1. The worst case scenario (in which no control measures are instituted) was 83,000 dead (1.67% population mortality rate, as per their Table 2).  By contrast, the worst case death toll (with no control measures) in the many papers of Professors Baker and Wilson (who were the most significant advisers to the government at this time) was 30,600 (in the Baker et al paper of 23 March).  Hendy et al do not even cite this paper, which predates theirs, let alone explain why their worst case figure is almost three times that of Baker et al.  The usual practice in academic work is to cite relevant existing work, and explain why your approach is better.  The need for this is amplified by the fact that none of the Hendy et al co-authors is an epidemiologist, while all co-authors of the Baker et al paper are.

2. The set of control strategies examined did not include lockdown (closing down all but essential businesses as well as all the restrictions described by Hendy), and yet Hendy et al concluded that deaths could be limited to 20 in the highest control state examined by them.  The only places of work that are closed down in any of the control states in Hendy’s Table 2 are schools and universities.  Since it took lockdowns on repeated occasions to achieve New Zealand’s covid death toll to date of 27, Hendy’s belief that this could be achieved without lockdowns would seem to have been far too optimistic. Interestingly, in Baker et al’s paper of 23 March, the authors do not define the restrictions involved in their high control scenario (which they call “eradication”) but the lack of specification of the restrictions at least allows for the possibility that it involved lockdowns.

3. None of the control strategies examined by Hendy et al corresponds to Level 3 or Level 4, despite these levels having been defined by the government on 21 March 2020, which was four days before the Hendy paper was released.  So, by the time the paper was released, it was already superseded by the events of 21 March.

4. The costs of adopting different control strategies are not even mentioned, let alone quantified.  Nor was there any conversion of predicted deaths to life years lost, nor valuation of this in accordance with standard methodology in the medical literature.  Again this contrasts with the Baker et al paper.

The next significant paper by Hendy et al was on 21 October 2020 and was concerned with the economic costs of the Level 3 August 2020 Auckland lockdown relative to those of an alternative Level 4 lockdown:

The paper assumes adoption of the government’s elimination strategy and is only concerned with the question of whether Level 4 restrictions would have been more or less costly (in lost GDP) than the Level 3 restrictions actually adopted in Auckland (Level 4 restrictions cost more per day than Level 3 restrictions but are likely to end sooner).   They find a modest such advantage to Level 4, because the expected time in lockdown to reach their epidemiological target is shorter in Level 4, which more than compensates for the higher costs per day.  This seems to be the first paper from Hendy et al that considers the costs of competing policies, but none of the co-authors appears to have any expertise in economics. The most interesting features of the paper are:

1. Despite considering the costs of these two options, the paper does not accord with the standard methodology in the medical literature of assessing the comparative deaths of the two options and converting this to a cost per QALY saved.

2. The data in their Tables 1 and 2 does not reconcile.  For example, Table 1 states that the cost per day in Level 3 is $57m, Table 2 gives expected days under Level 3 restrictions as 23, implying a cost of $1.3b, but Table 2 gives a cost of $1.8b instead.  The same problem applies to the Level 4 restrictions.  I raised this point with the lead author (Rachel Binny) on 17 November and received a reply from Professor Hendy but he did not address this issue over the course of several emails (in which I reminded him about the point).  I therefore presume that Table 2 is in error.

3. Page 8 of the paper says “Figure 2B shows the economic cost of the outbreak for a particular probability of elimination in the cases where the elimination was successful.”  This is not correct. The Figure is premised on exiting lockdown when cases have fallen to a level at which the probability of elimination has fallen to a particular level, and shows the economic cost for the expected lockdown period for a particular probability of elimination. Whether elimination was subsequently achieved is irrelevant to this calculation.  I also raised this point with the lead author (Rachel Binny) on 17 November and received a reply from Professor Hendy but he did not address this issue over the course of several emails (in which I reminded him about the point).

4. The authors acknowledge that their analysis does not consider the “..longer term economic costs of the measures..” (Executive Summary) and that “These factors may take the analysis to a different conclusion.” (page 10).  What then is the usefulness of the analysis?

5. Despite limiting themselves to the question examined, they note in passing that cost benefit analyses such as those performed by Heatley (2020) and Lally (2020) “…might be useful for informing a mitigation strategy but are not useful for a decision maker considering or following an elimination strategy” (pp. 4-5).  This seems to be accepting that cost-benefit analysis might be appropriate for choosing between mitigation and elimination strategies, as was the focus of Lally (2020), whilst denying its usefulness in choosing between Level 3 and 4 restrictions.  However, even if one has decided on an elimination strategy, for whatever reasons, there are competing variants of it, as Hendy et al recognises in comparing a Level 3 and Level 4 response to the Auckland outbreak, and cost-benefit analysis should also be used to choose between them, as Heatley does and Hendy et al do not.

6. Hendy et al refer again later to the cost-benefit analyses of Heatley and Lally, and state that “Combining our approach….with these more in-depth economic analyses may be useful in informing future responses.” (page 10). This seems to be accepting that cost-benefit analysis may be useful for choosing between Level 3 and 4 restrictions, thereby undercutting the contrary claim quoted in the previous point.

7. The equivocal comments by Hendy et al quoted in the last two points (“may” or “might”) suggest a lack of confidence on the part of the authors about basic economic issues that anyone offering policy advice ought to be confident about. This is understandable in view of none of the authors having any apparent expertise in economics, but it is harder to understand why they would offer policy advice about matters that they are so uncertain about.


Vaccination rates – some thoughts on modelling

There’s been some hysterical modellers claiming that even
with high rates of Pfizer vaccination, there will still be a large number of deaths.
Ironically, their models have opened the way in New Zealand to questioning the value of Covid vaccines.
We don’t need notoriously unreliable models, because we’ve got actual trial data. Trial evidence is superior to all other epidemiological evidence, and particularly so for projected models. We shouldn’t be relying on models now that we have so much observed data, including trials.
The latest Pfizer data reveals that there is a 7% increase in the overall fatality rate in vaccinated people compared to the unvaccinated.
As we said in a recent post:
The best evidence of overall effect on death comes from the latest update of the Pfizer trial which shows slightly more overall deaths (15/21,926) occurred in the vaccinated group than in controls (14/21,921). This is important, since the outcome doesn’t just count successes (reduced covid ‘cases’), but also includes the possibility of vaccine harm, evaluating the effect of the vaccine on overall survival. This means the best evidence thus far indicates a 7% increase in risk of death, comparing the vaccinated to the unvaccinated. Yes, the numbers are small, and these results are compatible with a wide range of vaccine effects, but it seems strange that this important information is relegated to the study appendices and is absent from the summary. Most of us are more interested in our overall longevity, rather than being solely focused on avoiding covid-19. The Prime Minister’s claim (52’:27”) that the vaccine is “saving lives” is sounding hollow, from the best possible epidemiological evidence: Pfizer’s own trial.
Another publication points out that more severe adverse outcomes occurred in the treated than the untreated in all three vaccine trials.
The claims of the New Zealand modellers and Prof. Rod Jackson ignore important facts:
1. The age distribution of deaths with Covid is about the same as background.
2. Delta is not much different
It is not clear that ‘Delta’ is worse than any other form of Covid.
3. Vaccines and lockdowns are not working
Jackson states that there are only two ways to ‘deal with delta: lockdowns and vaccines’.
As we have been saying from the start, lockdowns don’t work.
Vaccines have not been successful in halting the Delta variation.
With all this data available, why are we still living in fear?
While it was easy for authorities, media, and professional and amateur worriers to start the irrational fear that has dominated that past 18 months, it has been extremely hard to stop it.
Many of those who started it, and modellers were chief among them, don’t yet want it to stop.

Notes on Covid vaccines in young people

There have been reports of deaths in New Zealand teenagers within weeks of being administered with the Comirnaty product.

It is concerning that there has been a concentration of unusual fatal events in teenagers in a short space of time, coinciding with the roll-out of the experimental product with only provisional Medsafe approval.

There’s not yet enough information to make conclusions on these specific cases, but there are reasons for concern.

The first is medical. The timing and the type of health event, raises the chance of connection – at the very least to the point of acknowledgement and urgent investigation.

Heart attacks or myocardial infarctions, to use the technical term, are exceedingly rare in teenagers.[1] Generally, only case-reports are described and they often are associated with other factors, such as illicit drug use.[2] Similarly, another possibility, community acquired vein clots in otherwise well children are extremely rare. A search of cases at The Royal Children’s Hospital in Melbourne from 2007 to 2015 yielded only eleven.[3] The term ‘heart attack’ may refer to myocarditis or heart muscle inflammation, which has been linked to the vaccine by the government’s own medicine regulator.[4]

It is not clear whether proper investigations have taken place. The lack of interest is at odds with growing evidence of harm in young people after the Pfizer mRNA injection overseas. One study highlights a case-series of heart inflammation in 13 US adolescents in Washington state[7] with a median onset three days after the vaccine. A cohort study from Spain shows a three-fold increased risk of any vein clot after the second dose, compared to unvaccinated people.[8] Overseas reports of injury post-vaccination are like those described here in NZ. Singapore media described a case of heart inflammation as a ‘heart attack’ in a 16-year-old. Their government has agreed to pay the teenager $225,000 in compensation.[9]

We need to remember that the risk of death from covid-19 in teenagers is almost zero, as is their overall risk of death in this country.[11] The evidence relating to young people dying within a fortnight of a vaccine must not be hastily swept under the carpet

That the deaths are being downplayed is the second concern. The willingness of authorities to act and say there is no connection, when they don’t have or provide information, is a very serious breach of their duty. It is an awful risk to take.

The response from government officials has been surprisingly dismissive.[5] In a recent newspaper article, director-general of health Dr Ashley Bloomfield stated that if there was “any possibility” of such a link, a health professional would have reported it. This is an extremely weak form of ‘argument from authority’ (essentially Bloomfield said that since no authority has reported it, it didn’t happen).

The principal of another school stated that he understood the death was “due to a suspected heart attack – not COVID”. This excuse sidesteps the core question, and is typical of preparedness to use non-experts saying silly things when they back the pro-Covid vaccine narrative.

Another article quoted the Prime Minister: Jacinda Ardern said there have been no deaths to any teenagers in New Zealand related to getting vaccinated and encouraged New Zealanders to continue getting vaccinated.[6]

Further information about these cases is clearly in the public interest. Were autopsies carried out? What were their results? What was the working diagnosis? A full investigation and disclosure of the evidence for vaccine harm is surely the only prudent response given the gravity of these events. Are there other deaths after the injection that are not reported?

This cluster of deaths should make us all take a sober look at the real risks of this experimental injection and dig deeper into the details of these deaths, as our next generation depends on us for guidance.











Bridle busts open nonsensical vaccine attitudes and rules

A passionate and dispassionate dissection of Covid ‘vaccines’, and ridiculous mandates and use of them by authorities, from Byram Bridle, Associate Professor of Viral Immunology, at the
University of Guelph.

2021-09-17 – Open letter to the president of the U of G_B.Bridle

Vaccine targets no use in Covid-19 policy


Many areas of the world are now in a race to achieve high coverage of covid-19 vaccination. Some commentators in New Zealand are now criticising the government for not rolling out  fast enough. Given the high efficacy of many vaccines, this seems like a sensible strategy, but is it?

The government recently asked some of New Zealand’s epidemiology experts “Is an elimination strategy still viable as international travel resumes or are we going to need to accept a higher level of risk and more incidence of COVID in the community”. The specialists concluded that: “There is no doubt that this strategy has served us well”, comparing deaths in New Zealand attributed to covid-19 of 26 to 10,000 in Scotland. The way out was through high levels of vaccination. The document assumes that elimination is the ‘optimal’ strategy and further incursions, we are assured, will be ‘stamped out’ as we achieve high levels of vaccine induced immunity.

Will this really eventuate? In terms of rapid vaccine rollouts, Iceland is a counter example. Icelanders have now vaccinated 69 or 81% of their population, depending on whether you consider the whole population or only those eligible for vaccination (12 years and over). Almost all Iceland’s older generations are now vaccinated (99% coverage of 70 to 79 years), yet the younger generation has slightly lower coverage (78% of 30 to 39 years).  However, the vaccination records of covid-19 cases there tells another story: 73% of cases are fully vaccinated. This figure is inconsistent with the trial evidence of efficacy of the vaccine being 95% in reducing symptomatic infections (95% confidence interval: 90.3 to 97.6%). If this efficacy were correct, covid cases would be expected to only yield a small fraction of people with records of full-immunisation [(69% – 95% * 69%)/(1 – 69% * 95%) = 10%]. As almost three-quarters (73%) of recent cases in Iceland are fully vaccinated the efficacy obtained in the trial does not match the reality of the roll-out.

Others are noticing similar results: a recent case-series in the US also showed 74% of cases were vaccinated, with PCR cycle threshold values, roughly assumed to be equivalent to infectivity, similar in vaccinated and unvaccinated cases.

A case is being made for continuing vaccination since deaths may be prevented in those vaccinated. However, in the UK, a Public Health England recent report shows that of all dominant delta variant cases occurring from 2 February to 3 August 2021 (n = 300,010), 15.7% (47,008/300,010) were fully vaccinated compared to 50.3% (151,054/300,010)  unvaccinated. The remainder were either partially vaccinated or their status was unknown. A total of 741 deaths occurred in the delta cohort (0.25%; 741/300,010) within 28 days of testing PCR positive, with 90% of deaths (670/741) occurring in those aged over 50 years (figure; five unlinked cases are removed). The outer grey square represents the total cohort who tested positive for delta variant, with the blue rectangle the cases aged less than 50 years, the beige those who had been fully vaccinated, the dark green those who were hospitalised and the light green the deaths. One can immediately appreciate that deaths are few in the delta cohort and that most people do not need hospital treatment, even in the over 50 age group. This means that delta is hardly the “game changer” the Prime Minister has talked of.

Analysis of the delta cohort points to differential associations between exposure to the vaccine and death within a month. When the cohort is divided by age, deaths associated with covid-19 are 1.57 times (95% confidence interval (CI): 0.85 to 2.89, not significant) more likely in the vaccinated group under 50 years, compared to unvaccinated, whereas in the older bracket the vaccinated are 70% less likely to die from covid-19 compared to the unvaccinated (95% CI: 84 to 64%).  The vaccine’s ability to prevent covid-19 deaths in younger age groups among people with the delta variant is certainly questionable from these data. It must also be remembered that these calculations are crude in the sense that they do not account for comorbid status of delta ‘cases’.

Figure. Scaled rectangle diagram, illustrating the fatality proportion of the UK delta variant case cohort, by vaccination status, age and need for hospital care. Some counts of small cell values and those with uncertain vaccination status (n = 31,841) have been omitted. This includes 13 deaths occurring in the ‘fully vaccinated’ under 50 years, 56 in the ‘unvaccinated’ group under 50 and 7 were unlinked, making 741 total deaths.

The best evidence of overall effect on death comes from the latest update of the Pfizer trial which shows slightly more overall deaths (15/21,926) occurred in the vaccinated group than in controls (14/21,921). This is important, since the outcome doesn’t just count successes (reduced covid ‘cases’), but also includes the possibility of vaccine harm, evaluating the effect of the vaccine on overall survival. This means the best evidence thus far indicates a 7% increase in risk of death, comparing the vaccinated to the unvaccinated. Yes, the numbers are small, and these results are compatible with a wide range of vaccine effects, but it seems strange that this important information is relegated to the study appendices and is absent from the summary. Most of us are more interested in our overall longevity, rather than being solely focused on avoiding covid-19. The Prime Minister’s claim (52’:27”) that the vaccine is “saving lives” is sounding hollow, from the best possible epidemiological evidence: Pfizer’s own trial.

The policy response to the recent surge in cases in Iceland is to extend vaccination to pregnant women and impose further restrictions. The UK, in contrast, is dropping restrictions, despite a recent spike in overall case-numbers.  As New Zealand is once again thrown into costly lockdowns, we need to ask whether it is appropriate, given the evidence.

We now have a group of scientists advising the government that cannot see any other strategy apart from elimination as ‘viable’ or ‘optimal’. This is understandable, as they have committed the country to this course of action, one that has cost us at least NZ$50 billion. We must now recognize that other courses of action are viable. Sweden, Florida, and Texas demonstrate this. Analysis of excess mortality in Sweden for 2020 has shown a 3 to 8% increase from background which are attributable to past mild influenza seasons. The rush to vaccinate must now be balanced by the questionable efficacy of vaccines demonstrated in Iceland, the accumulating evidence of vaccine-related adverse effects, including the 350 serious reactions on government websites. The enthusiasm for more lockdowns must also be questioned, given evidence of  business closures, queues at food banks and the extra 43,000 kiwis on jobseeker support since March 2020.

As we said from early 2020, the path forward lies not in a medical intervention, but rather in a realistic assessment of the threat posed by the virus, based on such evidence as the distribution of age of death with covid-19 being similar to background mortality. Our efforts should be best focused on protecting the most vulnerable, implementing early treatment protocols, increasing capacity in our hospitals, while the majority of those of working age and younger people return to normal life. Overseas data clearly now show that vaccines are not a way out.

Reflections on the Skegg report pt.2

Dr Martin Lally

Director, Capital Financial Consultants Ltd

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).

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:

  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?


BMJ critiques Pfizer data: efficiacy waning

Here’s at link to Peter Doshi’s devastating BMJ critique of the Pfizer vaccine data. Which leaves the Israel experience as our most reliable current guide – and Israel is reporting efficiacy below 40%.
In short, there is “no reported data past 13 March 2021, unclear efficacy after six months due to unblinding, evidence of waning protection irrespective of the Delta variant, and limited reporting of safety data. (The preprint reports “decreased appetite, lethargy, asthenia, malaise, night sweats, and hyperhidrosis were new adverse events attributable to BNT162b2 not previously identified in earlier reports,” but provides no data tables showing the frequency of these, or other, adverse events.)