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

Simon Thornley

6/7/2021

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

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

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

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

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

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

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

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

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

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

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

NZ Doctors speak out

NZ doctors speaking out with science: a brave new declaration by NZ doctors and concerned citizens.

https://nzdsos.com/

Why we spoke out

Martin Kulldorff explains the rationale of the covid skeptics who feel compelled to speak out.

It has been hard to find any prominent NZer prepared to resist the covid fear-mongering and the Covid elimination strategy. Fortunately, those so vehemently in favour of fear and ‘zero covid’ plans have recorded their opinions for when the future comes looking to find blame.

https://www.spiked-online.com/2021/06/04/why-i-spoke-out-against-lockdowns/

I had no choice but to speak out against lockdowns. As a public-health scientist with decades of experience working on infectious-disease outbreaks, I couldn’t stay silent. Not when basic principles of public health are thrown out of the window. Not when the working class is thrown under the bus. Not when lockdown opponents were thrown to the wolves. There was never a scientific consensus for lockdowns. That balloon had to be popped.

 

Instead of understanding the pandemic, we were encouraged to fear it. Instead of life, we got lockdowns and death. We got delayed cancer diagnoses, worse cardiovascular-disease outcomes, deteriorating mental health, and a lot more collateral public-health damage from lockdown. Children, the elderly and the working class were the hardest hit by what can only be described as the biggest public-health fiasco in history.

Meta study: Lockdowns “greatest peacetime policy failure”

http://www.sfu.ca/~allen/LockdownReport.pdf

An examination of over 80 Covid-19 studies reveals that many relied on assumptions that were false, and which tended to over-estimate the benefits and under-estimate the costs of lockdown. As a result, most of the early cost/benefit studies arrived at conclusions that were refuted later by data, and which rendered their cost/benefit findings incorrect.

Research done over the past six months has shown that lockdowns have had, at best, a marginal effect on the number of Covid-19 deaths. Generally speaking, the ineffectiveness of lockdown stems from voluntary changes in behavior.

Lockdown jurisdictions were not able to prevent non-compliance, and non-lockdown jurisdictions benefited from voluntary changes in behavior that mimicked lockdowns.

The limited effectiveness of lockdowns explains why, after one year, the unconditional cumulative deaths per million, and the pattern of daily deaths per million, is not negatively correlated with the stringency of lockdown across countries.

Using a cost/benefit method proposed by Professor Bryan Caplan, and using two extreme assumptions of lockdown effectiveness, the cost/benefit ratio of lockdowns in Canada, in terms of life-years saved, is between 3.6–282.

That is, it is possible that lockdown will go down as one of the greatest peacetime policy failures in Canada’s history.

Sam Bailey critiques NZ media coverage

https://odysee.com/@drsambailey:c/Vaccines-Lies-And-Smears-Odyssey-Comp-2:c

Note also:

Stuff promotes Covid shots: https://web.archive.org/web/20210317173856/https://www.stuff.co.nz/national/health/coronavirus/124508789/stuff-wins-funding-to-counter-covid19-vaccine-misinformation

NZ Government puts $50 million into the media: https://www.rnz.co.nz/national/programmes/mediawatch/audio/2018743793/government-moves-on-short-term-relief-for-media

An open video from NZ GP Damian Wojcik

Open letter from Mary Hobbs, NZ author

An Open Letter to Charlie Mitchell (Stuff)

 

Media stoking fear

Indian Covid ‘resurgence’ shows again how media and some scientists have stoked fear without just cause.
Three stories in the NZ Herald illustrate how the natural and necessary evolution of discovery and understanding about the SARS-CoV2 virus is twisted by the immediacy and uncertainty of daily media coverage into unnecessary fear.
On 26 March NZ Herald carried a story warning of a “double mutant” variant of SARS-CoV2 in India.
 
On 28 April NZ Herald carried story claiming Indian “covid crisis poses threat to the whole world”.
 
On 20 May NZ Herald carried story headlined: Indian variant may not be as dangerous as we thought, admit scientists 
Over those three months a lot of fear was generated by poorly-founded scientific commentary and media worst-case angles. This fear contributed directly to NZ’s border policy (travel from India suspended), and to public attitudes to other Govt policy such as long term border and MIQ management, international travel, masks and vaccines.
This is an illustration of the longer story of the world’s response to SARS-CoV2: a push-pull tangle of emotion, speculation, incomplete and irrelevant data, narratives pretending certainty, group-think, safetyism and political ideology.

Analysis of NZ serology study

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

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

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

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

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

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

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

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

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

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

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

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

Fact-checking Covid vaccine experts

Simon Thornley

18/04/2021

1014 words

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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