Emergency Powers: [4] In a Controversy, who controls the Science? (AKA the modelling)

From my April 2022 paper COVID-19 Emergency Powers: The New Zealand State, Medical Capture & the Role of Strategic Ignorance

Chapter 4.

The complete paper in PDF form is available at www.TalkingRisk.NZ and a brief review is published on Rumble. My gratitude to Brownstone Institute for publishing a related article this week.

From the early days, the narrative of control was focussed on prevention of transmission, rather than a narrative of care. Professor A.C. Grayling has drawn attention to an inevitable issue that will always plague democracies,

‘all human institution can be ‘gamed’ or manipulated in the interests of those with greatest access to the machinery of those institutions.’

Many governments keep research and science institutions stand alone or connected to the education sector. the majority of science funding in New Zealand is directed through the Ministry for Business, Innovation and Employment. Overarching science policy directs New Zealand’s research, science and innovation system to prioritise excellence, investment return and the production of innovation (patents are a proxy for GDP). Since the advent of national systems of innovation some twenty years ago, New Zealand’s research and science communities, their expertise and cultures of decision-making relating to science production, have adjusted to Ministry directed expectations that prioritise innovation. Science policy has produced funding cultures which find it easier to finance technical research which might result in the development of an innovation (a product, process, good or service).

Funding environments are ultracompetitive, and unconventional or non-normative scientific research outside norms of scientific excellence such as complex, interdisciplinary work is more difficult to secure. Current and legacy policies have resulted in directing knowledge production towards digital technologies, biomedical science and genetics, which might promote economic growth through business development, and away from science that untangles the drivers of health and disease in humans, and in ecological systems.

WE DON’T DO BAD NEWS ON TECH

It is very unlikely a researcher or scientist in Aotearoa New Zealand will draw attention to the adverse effect of modern technologies. New Zealand’s research and science system cannot help but be techno-optimistic, as there is no safe place to research or produce science that might explore the adverse effects of novel technologies (also known as novel-entities) including pharmaceuticals and genetically engineered products.

The current institutional structures make it enormously difficult to weigh the benefits of public health research when exciting economic drivers such as prospective returns from medicine and biotechnologies divert research funding away from uncomfortable knowledges. When it comes to human technologies and pollutants that harm our heart, our endocrine system or contribute to cancer risk, the harm can arise before conception, during gestation, and childhood. This harm in vulnerable developmental periods can lead to neurological delays and greater predisposition to disease decades later. But we don’t actually know how to navigate these uncertainties in New Zealand, and to a very big degree, we don’t talk about them.

Over this time, health research in the physical sciences has been shepherded towards biomedical research that is translatable inside the health sector. For scientists on the ground, this means that realistically, funding will come if they propose scientific research that has a biomedical application. Over this 20 year period, the institution of health research in New Zealand has become predominantly medicalised. This has acted as a feedback loop into the policy and medical community. It’s meant that it has been enormously difficult to draw attention to the drivers of human health risk. In New Zealand, our predominant illnesses are obesity, and obesity related metabolic disease, which crosses into cardiac-related health risk. It’s now very, very clear that environment drives health and disease, not genetics or access to medicine.

The capacity of the science system to inform relevant Ministries and regulatory authorities, and guide policy to make important decisions to protect and promote health, is decoupled, because the science funding system still looks at funding by individual disease, and doesn’t make it easy for physical scientists to get funding to look upstream at the drivers of disease.

A failure to address the environmental drivers of disease, not only increases risk for non-communicable diseases – but increases risk from communicable diseases including Covid-19. One of the many reasons, is that people with obesity and metabolic diseases have greater levels of inflammation in their body, and the bodies efforts to mediate that inflammation, mean that their nutritional and biological resources are used up doing this job, and there are less resourced available to fight early stage infection, and prevent, for example, a respiratory virus descending into the lower respiratory tract, and the consequent cascade of pathological conditions observed, when early treatment doesn’t address Covid-19 at an early stage. Unfortunately, no data scientists are engaged to explore the costs of nutritional deficiencies in childhood, risk for obesity, or the problem of polypharmacy in our multimorbid populations and tasked to track the costs at the individual and societal level.

Innovation mindsets might encourage cultures less suited to coping with socio-biological ethical dilemmas including the right to deny a medical intervention, particularly from a novel mRNA gene technology. Vaccination rates are established as a high-level health system indicator by the Ministry of Health. The system (which in 2020 replaced health targets) focusses on hospitalisation and medical treatment rather than, for example, reduction of obesity or mental illness.

However, when vaccination is a high-level indicator, the practice of vaccination is unlikely to be critically reviewed, even if a product is vastly different to existing vaccines. Criticism of all technology must be permitted if the public are to not just economically, but socially and culturally benefit. If public servants and citizens cannot criticise technology, any promise of wellbeing cannot be fulfilled. Vaccines are a fundamentally unsafe technology; they involve the injection of an antigen into a body. This is why vaccine manufacturers are indemnified.

AOTEAROA NEW ZEALAND’S COVID-19 SCIENCE ENVIRONMENT

When COVID-19 arrived, the government did not encourage a quorum of interdisciplinary experts with expertise in ethics, law, biology, medicine and epidemiology and public health to come together and transparently with differing perspectives and thrash out the ethical socio-legal issues around out in a safe forum – to understand how risk would be managed and evaluate the ethical implications of prospective measures.

Instead of data production in a school of public health, data production, or modelling was delegated to a institution lacking a culture and appreciation of the principles of public health. This continues in March 2022.

The case focus has dominated and captured how the risk was modelled, communicated and promoted for the following two years. This approach has sidelined important established principles of public health which reflects issues of rights and protection. Case or infection rate modelling, and to a much, much lesser extent, modelling of hospitalisation and death has been the process by which the Ardern government, contracted institutions and a few key elites have manufactured consent for policy measures driving the population towards surveillance and ongoing vaccination. In a government that claims to use science for evidence-based decisions, there has been a consistent and ethically problematic absence of literature reviews and discussion of the peer reviewed literature.

The age and health stratified risk status have predominantly remained outside public deliberation for the duration of the pandemic. From the very first moments, the public narrative on COVID-19 risk was structured around the idea that 100% of the population were susceptible to Covid-19 ensuring a focus on around prevention of cases, not of hospitalisation and death. This locked in a narrative of control of a respiratory virus, rather than population level protection of hospitalisation and death.

From the very start, risk was weighted towards older adults. One of the early modelling papers recognised that that perhaps 88.9% of deaths would occur in the 60 plus age group. Exactly two years later, 81% (or 35 out of 43) of the Covid-19 caused deaths are in the 60 plus category.

The Department of Prime Minister and Cabinet has directed funding to understand risk in the COVID-19 pandemic. The COVID-19 business unit was established within the Department of Prime Minister and Cabinet. This unit was not only responsible for strategy and policy, operational co-ordination and public communications, it was established as the data hub,

Data analytics, monitoring, reporting and insights - including coordinated reporting to provide a tested, robust and consistent source of information, and provide agencies with cross government developed modelling and operational trends.

While initially funded by the MBIE, the Department of Prime Minister and Cabinet currently directly fund and contract the University of Auckland based institution Te Pūnaha Matatini and the COVID-19 Modelling Aotearoa cohort. Te Pūnaha Matatini, is not an institute with experience in infectious disease epidemiology nor does it exercise an appreciation of the long standing principles of public health, which have traditionally been incorporated into infectious disease modelling and planning strategies.

Te Pūnaha Matatini was established to explore and understand complex systems and uncertainty. COVID-19 work appears to be centred around conducting modelling using data supplied directly from officials. Their Sars-Cov-2 modelling has failed to take account of open-ended dilemmas inherent in risk modelling: complexity, uncertainty and ambiguity.

Astonishingly, the vast majority of modelling was not directed to infectious disease epidemiologists, who historically recognise a wide range of factors that are relevant to understanding public health risk, including the requirement that responses are proportionate to the risk. This includes the role of herd immunity and the potential for susceptible hosts to be most at risk and the potential for animals, soil and water to act as reservoirs. Infectious disease epidemiologists recognise the role of pre-existing conditions for increasing risk from infection. These issues were not considered in Te Pūnaha Matatini modelling.

Experts in epidemiology appeared to perform early minor roles in assessing risk throughout the pandemic, and they clearly drew attention to age stratified risk (and here). However, with the exception of Professor Michael Baker, who authored a couple of studies, the majority of work has been carried out by mathematical and data modellers.

Perhaps only 3 out of some 50 experts involved in modelling and policy appeared to be epidemiologists. New Zealand’s Covid-19 Technical Advisory Group did include one infectious disease epidemiologist, Professor Michael Baker. The Covid-19 Modelling Aotearoa team were comprised of mathematicians, and data analysts. No experts in public health appeared to have a leading role in any of this modelling. The team were distinguished by an absence of public epidemiologists.

Te Pūnaha Matatini have had two roles – modelling risk, and a second, known as The Disinformation Project, which is engaged to observe, track and analyse:

‘open source, publicly available data related to Covid-19 mis- and disinformation on social media, mainstream media, and in physical and other digital forms of information and knowledge dissemination.’

While a tumult of modelling papers have been released, we have not seen the release of literature reviews on new knowledge relating to the safety and efficacy of Comirnity, also known as research name BNT162b2. It is evident that the COVID Vaccine Technical Advisory Group was not particularly interested in a feedback loop from Medsafe, that might have highlighted safety and efficacy concerns.

Reviews could have updated the public on the scientific evidence on waning, the risk profile of the spike protein, the potential for early treatment to be a tool when efficacy declines with new variants, and the risk-benefit profile by age and health status. This sort of research and science has not been undertaken.

Has the science engaged by the state conformed to norms of accountability and transparency, and norms of public health, including the principle of proportionality, the principle of first do not harm, and the principle of informed consent. The world is not very good at stewarding manmade inventions. We don’t provide a safe space for uncomfortable knowledges that might disrupt institutional activities. We’re not very good at funding science that particularly, draws attention to the social and environmental determinants of health and disease in childhood. The one institution that might have addressed this, Gravida, was defunded. Other institutions in this space prefer to discuss personal behavioural modalities, but don’t fund research that might impact economic activity. Because we are less likely to fund this science, it is then very difficult for the few institutional experts left, to speak up against the weight of institutional opinion.

Continue Reading: [5] Emergency Powers: Case Rate Rhetoric - were the public kept in the dark? here

References in full are on the original PDF at TalkingRisk.NZ