Category: Epidemiology

A feature of the covid-19 pandemic has been the relentless highlighting of cases, hospitalisations and deaths of covid-19 with very little context to help interpret the statistics. No matter what the mitigating factors, the story of a deathly and fearful virus is maintained by authorities, media and others protecting  the concept of a Covid-catastrophe. This, to our knowledge, has never occurred with any other disease in living memory.

The phenomena has even exaggerated the threat of the virus in the minds of academics and health specialists, who you would expect to remain sober. As an example, Professor Rod Jackson, a professor of epidemiology, in a NZ Herald article published August 18 2020. In the article, he claimed “Learning to live with Covid-19 is not a viable option.”

Jackson made several exaggerated claims of the severity of covid-19 that have gone unchallenged for 17 months. He stated that the infection fatality rate of the virus was between 0.5% and 1.5%, or about 1%. He stated that covid-19 is 20 to 40 times worse than the seasonal flu and that one in five infections (20%) would be hospitalised, and that one in five who were hospitalised would require intensive care. That means 4% of hospitalised cases will require intensive care (1/5 * 1/5 = 1/25 = 4%).

In reality, the proportion of cases requiring hospitalisation in New Zealand, at the time of writing (25/11/2021) is ~57/5213 cases = 1%. This is a 20-fold difference in risk of hospitalisation after testing positive for covid-19, comparing Jackson’s estimate to Ministry of Health reports. Rather than a 4% risk of need for intensive care, the risk is now 7 in intensive care/5,213 current cases = 1.3/1,000 or 0.13%.

The difference in severity of covid-19 conveyed by Professor Jackson compared to observed data may be displayed in Euler diagrams consisting of concentric circles whose areas represent numbers in each category of severity below (figure 1 for Jackson’s estimates, figure 2 for current government figures and figure 3 for pre-vaccine era figures). In each figure, the area of the outer circle is proportional to the total count of covid cases, the grey indicate those who needed hospital treatment, the light blue intensive care and the red deaths (taken as 1% case-fatality for Professor Jackson, and estimated by using 5,213 current cases * 41 deaths/10,789 cumulative cases in New Zealand (11/November/2021)).

These diagrams demonstrate the distorted perspective portrayed by experts and health authorities, compared to the official reported reality. The difference is stark.

Figure 1. Professor Jackson’s estimated proportions of cases needing hospitalisation, intensive care and who would ultimately die with covid-19 in the New Zealand media, August 2020.

Notional 10,000 cases used for illustration.

Figure 2. Actual severity of covid-19 cases in New Zealand, 25/Nov/2021.

One possible explanation for this discrepancy is that covid-19 cases in New Zealand now are mitigated by the widespread use of the vaccine. However, figure 3 below is based on an earlier description of the epidemiology of New Zealand covid cases from February to May 2020, before the vaccine era. This indicates only 4%, rather than Jackson’s 20% of cases needed treatment in hospital. Reality was already five times lower than Jackson’s figure. The admissions to intensive care were 0.67% of all cases, six times lower than Jackson’s estimate. Also, one can see (figure 2) that the many of the apparent deaths with covid-19 did not qualify for intensive care treatment, due to age and comorbidity. The figures given by Jackson have never been questioned for accuracy or corrected. Jackson also talked of infections rather than ‘cases’, on which the Lancet paper he drew from was based. This means the reality departs even further than Jackson’s depiction indicates.

Figure 3. Severity of covid-19 cases in New Zealand, February to May 2020.

To make sound policy, supported by a well-informed public, health authorities, and the media must convey an accurate sense of the severity of covid-19.

The threat needs to be estimated from true counts, rather than conjured-up figures. The diagrams convey how far reality has been warped.

It is clear now that many predictions, models, estimates and beliefs did not come to pass. The investment in the famed ‘elimination strategy’ is now not worth the paper it was written on. The lack of scrutiny on doomsday predictions has adversely affected our perception of the reality of covid-19 and our collective ability to respond to it appropriately.

We’ve been wondering why this distortion is occurring, and why so few people seem to care. The factor that stands out to us, and that the case of Professor Jackson illustrates, is that no one loses by highlighting the worst and downplaying the best. There are no questions, no re-assessments, and no penalties for being wrong, if you follow and contribute to the story of a deadly virus.

Should caution be exercised in the rollout of covid-19 vaccines to NZ children from 5 years old? History indicates rushed decisions lead to regret.

Gerhard Sundborn,¹* Simon Thornley,² Rupert Scott,³ René de Monchy,⁴ Matt Shelton,⁵ Byram Bridle⁶ 

Lecturer in Pacific Health, University of Auckland, Department of Pacific Health, New Zealand ¹

Epidemiologist/Public Health Physician, University of Auckland, Section of Epidemiology and Biostatistics, New Zealand ²

General Practitioner, Whangarei, New Zealand ³

General Practitioner and Psychiatrist, Tauranga, New Zealand ⁴

General Practitioner, Wellington, New Zealand ⁵

Professor of Viral Immunology, University of Guelph, Canada⁶

Corresponding author * email: g.sundborn@auckland.ac.nz

The New Zealand Ministry of Health have indicated that they are now actively considering the Pfizer covid-19 vaccine for New Zealand Children age from 5 to 11 years old.¹ This follows its approval for use in New Zealand children aged 12 to 15 years on Monday 21^st June, by ‘Medsafe’, New Zealand’s drug regulator.² Other countries including USA, Canada, China and the European Commission who have also approved the vaccine for children aged 12 to 15 years old. China has authorised vaccination for children from three years of age. However, the World Health Organization (WHO) advise that children and adolescents have milder disease than adults and therefore more evidence is needed on different covid-19 vaccines for this age group, which has prevented them from making general recommendations for their use.³ In the UK  the Joint Committee on Vaccination and Immunisation (JVCI) concluded that the health benefits gained by vaccination of 12 – 15 year old children are only marginally greater than the potential and known harms. And that this margin of benefit was too small to support universal vaccination of healthy 12 to 15 year old children.⁴ Since covid-19 itself poses little risk of fatality to children, and the exposure to a vaccine entails risks which are now poorly understood, we examine them in more detail here. Recently, an Auckland Professor of Epidemiology, regarding covid-19 vaccination stated:

“The Government has introduced (vaccine) mandates in health – total no-brainer. They’ve also introduced one in education for all the staff – total no-brainer. They need to introduce the same mandate for 12-and-over children”.⁵

To date, a decision to rollout the vaccine to children aged 5 – 11 years has not been made. We question the idea that vaccine mandates are a “no-brainer” particularly for children. Specifically, we believe that for children, emerging data indicates that such a policy will lead to more harm than good. We urge a precautionary approach be taken and that any plans for the vaccination of children be delayed for three important reasons.

Long-term safety and efficacy of the covid-19 vaccine is unknown: The first and most crucial point is that the long-term safety and efficacy data from the trial will not be available until 2023. Although short-term safety and efficacy data looks promising, this has only been tested in a small cohort of children, with 1,131 children receiving the vaccine at the time of writing.⁶ This means that detected adverse effects would only be those which are relatively common, and side effects, such as excess clotting that have led to the withdrawal of the AstraZeneca vaccine, for example, from many countries would not have been detected.⁷ This vaccine is one of the fastest to ever be developed and rolled out, taking less than one calendar year. Before this, the fastest approval was four years. Most take an average of ten to fifteen years from development to approval for clinical use.⁸

When we reflect on the 2009 swine flu pandemic a similar scenario occurred where the hastened development and approval of a vaccine took an astonishing 5-6 months once the new virus was identified.⁹ The vaccine was then administered widely, until 2011-12 when long term safety and efficacy data were available – from which studies indicated that the vaccine caused unacceptable rates of narcolepsy.¹⁰ This resulted in over a billion-dollars’ worth of these vaccines being destroyed.^11-13

Another more distressing example occurred in the 1976 swine flu outbreak at the US Fort Dix military base. The infection caused one death and 230 soldiers to become ill. This led to a hastily developed vaccine that was rolled out to approximately 22% of the US population. The resulting vaccine caused over 500 cases of paralysis and 25 deaths. The vaccine was far worse than the virus itself and observers thought that the government response was too fast, with important safety considerations overlooked.¹⁴

In the US there has been a dramatic increase observed in US government vaccine injury reports as evidence of vaccine harm. The 100-fold increase in post-vaccine deaths reported in temporal association to the rollout of the Covid-19 vaccines in late 2020 is perhaps best shown in the plot below.

Figure 1. Time series of monthly reports of post-vaccine deaths to the US VAERS monitoring system.

Such a rapid increase in reports should be cause for concern, particularly when the development and clinical testing of the vaccines has been so truncated, and adverse effects from wide scale vaccination are unknown.¹⁵  Conventional epidemiological knowledge confirms that medical adverse event databases generally under-report safety signals. In a United States study that compared augmented electronic monitoring of health records in the thirty days post-vaccination, with prompting of clinicians to report likely vaccine-related events to usual practice, the augmented system resulted in a 30-fold increase in vaccine-related incident reporting, compared to historical periods. ¹⁶ When considering whether the spike in adverse event reporting is related to increased rates of vaccination or harm due to the vaccine, statistical tests carried out by Rose et. al. indicate clearly that the deaths are clustered around the time immediately after the event, in a manner which is incompatible with what would be expected if such deaths were occurring due to background mortality risks (P < 0.001).¹⁷

Efficacy of the Pfizer covid-19 vaccine is reported to be 52% after the initial dose and 95% after the second dose which has been taken from interim data.¹⁸ However, these claims have been questioned by researchers in Israel who have seen a far lower than expected decline in cases following vaccination of over 75% of their elderly population. Rather than a 52% decline in cases they have seen a significantly lower reduction in cases by 33%.¹⁹ Further, the protection against new variants of the virus remains unknown. A study recently published in the Lancet has found being fully vaccinated does not reduce any transmissibility once infected with the virus, compared to unvaccinated infected people.²⁰

Very recently published evidence from overseas, where the vaccine rollout has occurred earlier than in New Zealand shows that vaccines are not resulting in enduring and lasting protection from the virus. A preprint Swedish cohort study (1.6 million people) which compares the risk of Covid-19 infection in vaccinated and unvaccinated people throughout the Covid-19 vaccination roll-out in the country from the 4^th of January to the 4^th of October 2021.²¹  Analysis of those who had taken the Pfizer vaccine showed that the effectiveness at preventing symptomatic infection waned from initial high levels to 47% in the period 121-180 days after the vaccine to no convincing effect beyond day 211 post-vaccination (23% reduction; 95% confidence interval, -2 to 41, P = 0·07), compared to unvaccinated people. This modelled decline in vaccine effectiveness is illustrated in the figure below. Such an effect was observed for all Covid-19 vaccinations used in the country, and observed for more severe health outcomes such as prevention of Covid-19 hospitalisation and death.

Figure 2. Estimated adjusted effect of vaccine to prevent Covid-19 infection after vaccination in Sweden.²¹ Solid line represents point estimate and shading represents 95% confidence interval. Overall, no beneficial effect is observed after 240 days (8 months) since vaccination.

The risk covid presents to children is negligible: The second reason against vaccinating children is the very small risk that the virus poses to this group.²² There is a 1,000-fold difference in mortality risk between comparing children with frail elderly people after testing positive for covid-19. It is extraordinarily rare for a child to suffer any significant illness from covid-19 and orders of magnitude more rare for them to die from this virus.²³ A prominent US epidemiologist likened the risk of a person less than 65 years old dying from covid-19 as remarkably uncommon and about the same as dying during a car journey from between 21 – 162 km each day.²⁴ This comparison shows that there is little personal risk posed by covid-19 to children and thus no reason to expose them to an experimental vaccine. Other arguments for vaccinating children are related to the threat of ‘asymptomatic transmission’. Up-to-date evidence, however, shows little evidence of this phenomenon in Wuhan, after 10 million people were screened by PCR for infection, whether or not they had symptoms.²⁵

Vaccine-associated risks that need further investigation: To date 18 countries including Canada, Sweden, Latvia, Germany, Italy, France, Spain, Denmark, Norway, and The Netherlands, have halted the roll-out of the AstraZeneca covid-19 vaccine due to concerns that it has caused blood clots in some recipients.⁶ There are similar concerns that the Pfizer vaccine may also cause clots. In Norway, 23 deaths of frail elderly people occurred shortly after receiving the Pfizer vaccine – with an investigation concluding that the vaccine was responsible for at least 10 of these deaths.²⁶ In Australia two middle-aged women also died after receiving the AstraZeneca vaccine, caused by rare blood clots in the brain.²⁷

Another risk from the vaccine for young people that have received the Pfizer or Moderna vaccine is myocarditis or pericarditis. In the US, more than 1,200 such cases have been identified in people younger than thirty years according to the Centres for Disease Control. A study in the United States showed that the risk of myocarditis after vaccination was 3.7 to 6.1 times higher than the risk of hospitalisation due to covid-19, even under conditions of moderate and high covid-19 incidence.²⁸     A more recent study shows a 13.6-fold (1,260%) increase in new cases of myocarditis after the second vaccine in 16 to 19 year old males, compared to background rates of the disease in the same demographic group between 2017 and 2019.²⁹ Other authors have questioned the use of vaccines in anyone less than the age of 65 years, since deaths attributable to the vaccine are likely to outnumber those saved by a factor of five.³⁰ For younger children, this calculation is even less favourable. These events have generally occurred within a week following receiving the second dose of the vaccine.³¹

Under-reporting into vaccine safety databases is common. In a United States study that compared augmented electronic monitoring of health records in the thirty days post-vaccination, with prompting of clinicians to report likely vaccine-related events to usual practice, the augmented system resulted in a 30-fold increase in vaccine-related incident reporting,³² compared to historical periods. This means that analyses based on such reporting systems are likely to be gross underestimates of the true burden of adverse events.

Other academics overseas have expressed concerns at the high rate of post-vaccine adverse effects reported in vaccine safety databases. In the UK ‘Yellow card’ system, for example, between 4 Jan and 26 May 2021, a total of 1,253 deaths and 888,196 adverse reactions post covid-19 vaccine were recorded, with 63 million people receiving at least one dose, and 24 million having had two doses.  This is roughly a 1/50,000 risk of death and 1/70 risk of adverse reaction after vaccination, assuming these reports are all caused by the vaccine. The author of the document, Dr Tess Lawrie, stated that based on these figures there was: “more than enough evidence … to declare the COVID-19 vaccines unsafe for use in humans”.³³

Table 1. Adverse Events for Covid-19 Pfizer vaccine verses influenza vaccine in NZ

Reviewing the latest Covid-19 vaccine safety report from Medsafe (New Zealand Medicines and Medical Devices Safety Authority) published on 9 October 2021³⁴ – a total of 27,651 Adverse Events following Vaccination (AEFI) have occurred. With 982 of these being Adverse Events of Special Interest (AESI) which are paid greater attention due to their seriousness. Most concerning is the number of deaths that have occurred following vaccination which now totals 91. When comparing the number of adverse events from the covid-19 vaccine to those reported to Medsafe for the influenza vaccine in 2019, ³⁵ we calculate that the Covid-19 vaccine adverse events rate is more than 31-fold greater. Further the influenza vaccine has no reports of Adverse Events of Special Interest, nor death following vaccination. From these data the covid-19 vaccine exposes those who receive it to far higher rate of adverse health consequences than that for influenza.

Summary: The Pfizer covid-19 vaccine remains experimental and is only provisionally approved for use in New Zealand. Long-term safety and efficacy data will not be known until 2023, and children are largely unaffected by the virus. Like the swine flu vaccine, a true understanding of the long-term side-effects of the vaccine remain unknown until these trials are complete. There are several serious side effects caused by current covid-19 vaccines whose risks are not fully understood. Basic safety biodistribution studies are missing,³⁶ with data from rodent models showing high uptake of nanoparticle delivery substrate in the ovaries of these animals.³⁷ Basic safety studies, that are a routine part of vaccine development were not carried out for this vaccine.

When considering whether to vaccinate children against covid-19, one must weigh the therapeutic benefits against the risks. With such little to gain, all children can possibly experience are the risks of the product, such as myocarditis. True estimates of risks from the vaccine are now not fully understood, although there are already several identified now including blood clots, myocarditis, and death. ^{38, 39, 34}

On balance, we believe that the known and unknown risks from the vaccine outweigh any benefits for children. Historical examples should lead us to pause and make a sober assessment of the risks, given the lack of benefit to children. We believe that it is best to wait at least two years for the long-term safety and efficacy results to enable a more informed decision to be made about whether to vaccinate children against SARS-CoV-2. Whatever else can be said about the decision to vaccinate children, it cannot and must not be considered a “no brainer”. No sober analysis would come to that conclusion.

This research did not receive any specific funding.

The authors declare no conflicts of interest.

References

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38. Joan-Ramon Laporte, Ermengol Coma, Francesc Fina, Luís García-Eroles, Xavier Vidal, Manuel Medina.  Vaccines against Covid-19, venous thromboembolism, and thrombocytopenia. A population-based retrospective cohort study. MedRxiv preprint; this version posted September 5, 2021. Date accessed: 4 October 2021. doi: https://doi.org/10.1101/2021.07.23.21261036

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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.

12/10/2021

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 vaccinated… I 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.

2. 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.

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. https://figure.nz/chart/SOBvdb4q1OXAaoLM-H9S6kQLicMFxLijb

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. https://www.nejm.org/doi/full/10.1056/NEJMoa2110345.

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

https://newsrescue.com/wp-content/uploads/2021/08/us-covid19-vaccines-proven-to-cause-more-harm-than-good-based-on-pivotal-clinical-trial-data-analyzed-using-the-proper-scientific-1811.pdf

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: https://www.timesofisrael.com/health-ministry-chief-says-coronavirus-spread-reaching-record-heights/

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. https://www.thegatewaypundit.com/2021/09/huge-uttar-pradesh-india-announces-state-covid-19-free-proving-effectiveness-deworming-drug-ivermectin/

For example, meta-analysis of trials (conventionally considered high level evidence) support the use of Ivermectin to reduce covid-19 mortality. https://lnkd.in/g3eMbaGU

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.

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.

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

3. 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”.
4. 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.
5. 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.
6. 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?