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Simon Thornley, Gerhard Sundborn, Ananish Chaudhuri and Michael Jackson

It is clear now that estimates of death from the Covid-19 pandemic were exceeded by factors of hundreds, if not thousands. This sparked public and political panic and led to our government enacting one of the most stringent lockdowns in the world.  Te Pūnaha Matatini predicted 80,000 deaths even with mitigation strategies, while the University of Otago team forecast 12,600 to 33,600 deaths.  Their best possible estimate was 5,800 deaths. The models encouraged the government to enact tight control measures. Now, we are largely over the epidemic, although some of the modelers have warned of secondary waves. New Zealand now has 22 ‘official’ Covid-19 deaths – a far cry from the forecast doom and gloom, with at least a 263 fold over estimate at this point. A recent article about Sweden followed suit, predicting a total of 60,000 deaths for that country, and decrying its decision not to lockdown.

How was it possible for these forecasts to be so erroneous? The interesting aspect, reading the modelling now, is that the number infected under each control policy scenario, including lockdown, was about the same. The Matatini group described 89% of the population being ultimately infected under even the most stringent strategy. The moment the handbrake was let off, another outbreak would occur. However, in the paper, the modellers themselves questioned the effect of lockdowns. They wrote:  “In other countries, including those that have instigating (sic.) major lockdowns such as Italy, there is as yet insufficient evidence that this has reduced [the epidemic]”. They then stated that “successful mitigation requires periods of these intensive control measures to be continued for up to 2.5 years before the population acquires a sufficient level of herd immunity.” The conclusion was that lockdowns were buying time for vaccination and learning from other countries. The modelling that justified the lockdowns was itself clearly stating that such policies were far from a panacea.

Models incorporated lockdown measures yet still predicted thousands of deaths. Critics will say that the lockdown is precisely why the models were so inaccurate. We were saved from catastrophe. Several lines of consistent statistical evidence does not, however, support this idea. US States that did not lockdown report lower Covid-19 cases and death rates on average than States that enforced heavier restrictions. Time trends in Europe show that lockdowns prolonged the recovery from the epidemic after these policies were enforced. Closer to home, it is clear that cumulative per capita cases and deaths of Covid-19 are lower for Australia than for New Zealand despite more relaxed restrictions over the Tasman.

The major factors behind these erroneous models include: (1) an overestimate of the infection fatality rate, and (2) a reciprocal underestimate of the immunity of the population.  Mathematical models of infections project the assumptions of the modellers into the future. They are mathematically elegant, but also based on many untested assumptions. Models assume a far greater degree of certainty than is true in reality.

The models used are built for infections which declare themselves, like measles. Covid-19 is different, it produces high rates of infections in people who feel well. Measles primarily affects young children who are unlikely to die from other causes. Covid-19, on the other hand, has shown to be most vicious at the other end of the age spectrum, specifically causing death most frequently in people at a mean age very similar to our life expectancy, about 82 years. This is curious, as it strongly suggests that the virus does not shorten life, since our life expectancy, or average lifespan, is similar with or without the virus on board. There is little mention of this in the Matatini document, and it is relegated to the appendix of the University of Otago report. Instead the Otago group talk of deaths of the magnitude seen in World War I. Given the age differences of deaths in World War I (mean about 27 years), compared to Covid-19, this must surely be classed as exaggeration.

Neither modelling team attempted to quantify loss of life in terms of ‘years of life lost’ (YLL), a standard epidemiological technique for comparing disease burden. Such statistics would have produced a totally different picture than headline death tallies, portrayed simplistically by the media. YLL is the sum of the differences between age at death and median life expectancy and weights death in the young higher than deaths in the old. Since Covid-19 deaths occurred at an average age in the 80s, this method of measurement would have produced a much less striking picture than the less sophisticated count that values infant and nonagenarian mortality as equivalent. Years of life lost from Covid-19 are extremely low, and pale in comparison to other risks to health, such as cardiovascular disease, diabetes and cancer.

As in the case of swine flu, antibody tests of the virus, are dialling down the infection fatality rate, to a range similar to influenza (0.03% to 0.5%). This contrasts from the genetic test evidence used by some commentators. This cuts down the dire predictions for Sweden by a large ratio. Since even people without antibodies have evidence of seeing the virus, the true infection fatality ratios are likely to be even lower than those adjusted for antibody tests alone. It is now clear that the dire prediction is very unlikely to be correct, since Sweden is now well into the downward slide of its epidemic curve for Covid-19 deaths. The value of observed data over modelled predictions is demonstrated here.

Related to the immunity tests, a strong, and very questionable assumption of the modelling is that we are all, as a population, susceptible to the ‘novel’ virus. Since from early on in the epidemic, it was clear that infection was more likely in the elderly, this was unlikely to be so. Recent evidence from immunologists strongly indicate cross-reactivity between “common cold” coronaviruses and SARS-CoV-2, which was present in at least 30% of people that don’t show other evidence of having seen the disease before. This theory is supported by a study that showed that 34% of a sample of healthy blood donors who did not have antibodies, instead had other evidence of immunity, with reactive T cells to the virus. Also, the finding of test-positive samples in France well before the epidemic ‘officially’ occurred, dents the ‘we are all sitting ducks’ theory.

In trying to make sense of these erroneous predictions we have to ask how this happened? We believe two basic features of the human psyche have been at work. The first of these is loss aversion: the desire to avoid losses that are right in front of us even if it means larger losses elsewhere or further down the road. The second is confirmation bias: that is the tendency to look for evidence that confirms one’s pre-supposition and discounts evidence that calls those beliefs into question. Of course, the 24-hour news-cycle, the cacophony of social media, the need for eyeballs, clicks, likes, tweets and retweets exacerbates these matters, since apocalyptic predictions are more likely to draw attention.

A casual look at an epidemic curve of Covid-19 deaths from Sweden shows that dire predictions, are extraordinarily unlikely to come to pass. Swine flu in 2009 was instructive as pessimistic models dictated an over-reaction. A post-mortem concluded that models “impress governments and provoke fears” and were overly pessimistic. Surveillance and reliance on biology and observed data were instead recommended. It seems that with Covid-19, we have learned little from this episode.[ST1] 

Several lines of evidence give us hope, to counter pessimistic modelling. One thing the inaccuracy of the models teach us is that our understanding of the behaviour of the virus is incomplete. Better understanding should translate to more accurate prediction. Epicurves by country in Europe and many parts of Asia, along with Australia and New Zealand are showing waning epidemics with insignificant secondary peaks. These patterns strongly suggest growing immunity in these countries, despite measured low antibody prevalence in some areas. The high rates of cellular and cross immunity explains this phenomenon. China, a very densely populated country, has now widely opened up after a lockdown and had few secondary waves. Japan is the same, although they had lighter restrictions. The sustained low number of cases when the curve falls strongly indicates that we can safely return to normality much more rapidly than was thought possible.

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In the aftermath of the Covid19 pandemic, it has been observed that countries led by female politicians have done better in terms of implementing social distancing measures. Examples include Angela Merkel of Germany, Jacinda Ardern of New Zealand, Mette Frederiksen of Denmark and Sanna Marin of Finland.

There is some controversy regarding the appropriate response and whether countries that locked down will experience additional waves once they emerge from lock down as opposed to a country like Sweden, which did not enforce such stringent policies. It is also the case that only a small number of countries around the world are governed by women. Extrapolating from small numbers is fraught with risks. 

But leaving those caveats aside, why were female leaders so much more pro-active in implementing social distancing policies?

Evolutionary theory may provide an answer. Evidence suggests that women tend to be more risk averse than men. An obvious consequence of this is that men tend to be hyper-competitive and over-confident. Faced with the risk of large-scale loss of lives, female leaders moved more swiftly to implement social distancing to minimize the risk. It is possibly not an exaggeration to suggest that the countries that have struggled the most in charting a consistent course (notably UK and USA) are led by competitive and over-confident men.

Evolutionary theory teaches us that a primary human drive is to pass on our genes to successive generations. Given that the amount of parental investment required of men is much less than that required of women, males can have many more off-springs than females. If a male can out-compete other males in terms of having a greater number of sexual partners, he can have more progeny. So, males have more of an incentive to compete, which in turn necessitates more risk taking, since there is always the possibility of injury or loss of life in such competitions for mates.  

In the animal kingdom, males are generally showier, more aggressive and more territorial. The level of male aggression is higher among animals that are polygamous as opposed to those who are monogamous. Males are also physically much larger than females in polygamous societies than in monogamous ones. Bull elephant seals are much larger in size than females and often engage in brutal battles for control of female harems.

Closer to home, Lise Vesterlund and Muriel Niederle show that women often tend to shy away from competing with men, even where there are no differences in their respective performance or ability. It is equally true that men tend to be over-confident and over-estimate their chances of success and therefore tend to compete “too much”.

There is now a large literature that looks at gender differences in risk aversion. Catherine Eckel and Philip Grossman point out that results from studies looking at either decisions made in abstract lottery choice experiments or in the context of financial decision making show women to be more risk averse. One example of this is that when it comes to retirement savings, a larger proportion of women prefer to invest in less risky options such as term deposits rather than stocks.

The same insight comes through if we look at actual investment behaviour of men and women.   Brad Barber and Terrance Odean study 35,000 investment accounts sorted by gender. They find that women outperform men mostly because men tend to be over-confident and trade a lot more. Women had turnover rates of 54 percent while for men this is 77 percent and the accounts with higher turnover performed worse than the average market return during this period.

In fact, there is also evidence to suggest that because women tend to be more risk-averse, they are less likely to generate asset bubbles (such as tech stock bubbles or housing bubbles) of the type that fueled the global financial crisis of 2008-09.

Helga Fehr-Duda and collaborators provide an alternative perspective on the supposedly greater female risk aversion by suggesting that men and women differ in the weights they assign to different probabilities. Women tend to underestimate probabilities of gains to a higher degree than do men, i.e. women are more pessimistic in the gain domain. The combination of these factors may lead to higher degrees of risk aversion for women.

It is also the case that such gender differences in risk taking tend to get compounded in times of stress. And existing evidence suggests that the such risk-aversion leads to the well-documented gender wage-gap, at least partly due to greater female reluctance to negotiate salaries. As Linda Babcock and Sara Laschever point out: Women don’t ask. The reluctance to negotiate may result in small differences between male and female salaries at the outset, but given that things like bonuses, outside offers and merit increases are all based on current salary, small differences in the beginning translate into large differentials a few years down the road.

However, here is a caveat: women who attend single-sex schools and those who grow up in matrilineal societies like the Khasi in India, exhibit similar risk-taking and competitive tendencies as men.

Bottomline: In times of crisis, whether it is a pandemic or a global financial crisis, when risk minimization becomes important, being led by women may be beneficial both for corporations and for countries. This also calls for greater diversity, both in the boardroom as well as in government for more reflective and deliberative policy making.

New Zealand’s Prime Minister Jacinda Ardern has won effusive praise in the overseas media for her handling of the Covid19 pandemic. (https://www.nytimes.com/2020/04/30/opinion/coronavirus-leadership.html)

Ardern is a warm, charming and empathetic human being and an excellent communicator. Unfortunately, the government she leads does not seem imbued with similar qualities.   

Back in mid-March New Zealand was in Level 2. Then we went to Level 3 for one day before moving to Level 4, with everything other than essential businesses closed down for four weeks. According to Oxford University Blavatnik School of Government’s Coronavirus Response Tracker, New Zealand enacted one of the most stringent lock downs along with India and Israel.

 (https://www.bsg.ox.ac.uk/research/research-projects/coronavirus-government-response-tracker)

Some commentators, including me, questioned at the time the sagacity of imposing a nation-wide lock down in a country with very low population density in general, particularly in the South Island.  

(https://www.newsroom.co.nz/ideasroom/2020/04/08/1119994/a-different-perspective-on-covid-19)

Reasonable people can certainly disagree on a decision. The government made the decision it thought was the best given the information at hand. But what was striking was the lack of consultation or justification as to why we needed to move to Level 4 so quickly. The legal basis for ordering the lock down is now in question; something that the government is now trying to clean up, ex post facto.

Two New Zealand legal experts wrote: “[The lockdown] imposes the most extensive restrictions on New Zealanders’ lives seen for at least 70 years; perhaps ever. No matter how ‘necessary’ these may be, we should expect such restrictions to have a clear, certain basis in law and be imposed through a transparent and accountable process.”

 (https://thespinoff.co.nz/covid-19/28-04-2020/the-legal-basis-for-the-lockdown-may-not-be-as-solid-as-weve-been-led-to-believe/)

Recently the government responded to questions on these matters by dumping a trove of documents in the public sphere. This was done on a Friday afternoon. Ministers have been asked to “dismiss” questions; ostensibly on the ground that the government enjoys public support and therefore, there is no need to engage with anyone offering contrarian views.

The New Zealand Ombudsman Peter Boshier commented that the move by the government, while not a violation of the legal principles of the Official Information Act, was certainly contrary to its intent. He also said that he was “horrified” to learn that in the aftermath of the pandemic the government had actually considered suspending the Official Information Act, before backing down. (https://www.stuff.co.nz/national/politics/121237698/coronavirus-officials-pitched-oia-suspension-during-covid19-lockdown)

Then, last week, the government passed “under urgency” the Covid19 Public Health Response Bill. According to one report “the bill went through Parliament in less than two days and with no select committee hearings (and) grants police warrantless entry to premises if they reasonably believe virus-related orders are being breached.” https://www.newsroom.co.nz/2020/05/13/1171049/covid-19-powers-approved-under-urgency

Both the Human Rights Commission and civil rights advocates have expressed strong reservations. A columnist for a leading daily suggested, rather diplomatically, that the government has “lost perspective”. https://www.nzherald.co.nz/nz/news/article.cfm?c_id=1&objectid=12331686

Not only does our government not trust us to do the right thing in public, they do not even trust us inside our own homes. The police can now enter homes without a warrant if they believe Level 2 restrictions are being violated. This vast expansion of the powers of the state is something that one expects in an authoritarian state; not a liberal democracy. Many authoritarian rulers think twice before enacting a law like this, which violates basic democratic principles including the protection against illegal search and seizure.

Caught in this rising tide of intolerance are thousands of migrant workers, who find themselves out of jobs and are now going hungry. The Deputy Prime Minister Winston Peters is the Leader of New Zealand First, a nativist party, which is part of Ardern’s governing coalition. Queried about the plight of migrant workers, he declared that they should probably go home. How? We live on an island and there are no flights!

(https://www.nzherald.co.nz/nz/news/article.cfm?c_id=1&objectid=12331405)

New Zealand is a founding member of the International Labour Organisation (ILO). Referring to migrant workers, Article 8 of ILO Convention 143 (1975) states:

1. On condition that he has resided legally in the territory for the purpose of employment, the migrant worker shall not be regarded as in an illegal or irregular situation by the mere fact of the loss of his employment, which shall not in itself imply the withdrawal of his authorisation of residence or, as the case may be, work permit.

2. Accordingly, he shall enjoy equality of treatment with nationals in respect in particular of guarantees of security of employment, the provision of alternative employment, relief work and retraining.

In the aftermath of the pandemic, concerns have been expressed about the expansion of state powers and the erosion of civil rights. It is unfortunate that New Zealand, usually known for its liberal stance on such matters, should fall victim to the same pressures. The Prime Minister’s resoluteness in the face of the crisis was a matter of pride for Kiwis but the turn toward authoritarianism by her government should be a cause for concern.