Imagine if the Olympic Games were currently being held in Wuhan, China. There would be widespread mentionings of it having been the starting place of the Covid19 pandemic, in December 2019.

But pandemics (not ‘global pandemics’; pandemics are global by definition, as are world wars) have two places of origin, though those two places could be the one-and-the-same. For Covid19, Wuhan was certainly the first place; the root source, to use a tree analogy. The second source is the base of the stem, the place from where a pandemic fans out and becomes almost unstoppable.

In the case of Covid19, the events in February 2020 in Milan and Cortina d’Ampezzo – the jewel of the Italian Alps – were the origins of the pandemic. Without their role, Covid19 might have been a contained epidemic such as SARS (2003).

Since the near-run-disaster that was the SARS-Cov1 panic in 2003, the amount of useful epidemiological work on coronaviruses has been minimal. There was clearly research work being done, including in Wuhan. But that was mainly on the zoonotic origins of coronaviruses, and not on the administration of outbreaks. SARS-Cov1 was a severe novel coronavirus. Novel respiratory viruses – such as the 1918 influenza pandemic – are lethal, spread fast, and are hard to contain. More lethal than Sars-Cov1 was MERS which emerged around 2012. Yet preparations for a respiratory-illness pandemic were focussed almost entirely on a new strain of influenza. No prep for a new novel coronavirus. SARS-Cov2 was ‘tricky’, in that – less lethal but more transmissible than SARS-Cov1 – it fell on the cusp between being dangerously lethal and dangerously transmissible.

Geographic Analysis

The pandemic events of 2020 were not – at least not in any popular awareness – subjected to a proper geographical analysis. Most of the initial outbreaks of the SARS-Cov2 virus which escaped China were largely contained. There were relatively small outbreaks in Japan, Hong Kong, Australia and Seattle in the United States’ northwest; in some cases transmitted by passengers from a few cruise ships. And larger but still largely contained outbreaks in South Korea and in Iran. These outbreaks came directly from China. The containment of the Iran outbreak was facilitated by the West’s generally hostile attitude towards that country as a geopolitical ‘bad guy’; Iran was easier than most countries for the West to quarantine.

More problematic were the outbreaks in Spain and Italy, which can also be traced back to January 2020. In Spain the initial outbreak, direct from China, was more in the south; most likely linked to escapees from China. There was relatively little subsequent movement across the land border into France, though Andorra experienced a separate outbreak. The main risk from the south of Spain was the United Kingdom, given that, for many British people, southern Spain is either their first or second home. It would have been relatively easy to quarantine British arrivals from Spain; the British authorities ‘dropped a ball’ by being tardy here.

The main blind spot was that Spain is a western country, and westerners had become ingrained in the supposition that pandemics (and all things bad) come from other countries; or, more accurately phrased, ‘countries of others’. Guard rails that were up for China or Iran or even Japan and South Korea, were not there for ‘threats’ from West European countries.

The notion came about that the pandemic radiated out of southern China, rather than having flowed out of all of the places which had experienced outbreaks. When eyes should have been watching Spain and Italy, they were still firmly focused on China, and in a finger-pointing way.

The West could have learned much from China’s data about the impact of the new virus in terms of the demographics of victims and non-victims, and the extent and duration of their exposures and their symptoms. However, the western countries were more predisposed to put up the shutters with respect to that amazing country.

A large part of the problem in the 1918 influenza pandemic was the high numbers of younger adults who caught it and died from it. Covid19 was never like that. Data from China showed that few younger people had died from Covid19; unless, that is, they had had sustained exposures. For younger people, and for society as a whole, it was better for otherwise healthy non-allergic people to have early and tentative exposures to Covid than to be on tenterhooks awaiting what became the inevitable, and would become worse the longer the wait.

Milano-Cortina

More problematic than Spain was the coronavirus outbreak around and to the east of Milan – the ‘tech’ centre of Italy, and the fashion centre – and the connection of Milan to the ski resorts during the peak of the ski season; indeed during the February school holidays in Europe. Milan is the most monied city in Italy. It is an important entry-point for affluent techies on business, and for sundry one-percenters. Once the epidemic began in Wuhan, many of the monied of and around Wuhan (many were foreign nationals) had the nous to ‘escape’ – including to Macao and Hong Kong – before the Chinese central government closed the ‘stable doors’.

Milan and environs became a hotspot for witting and unwitting coronavirus refugees – affluent exiteers – just at the time Europe’s ten-percenters were heading to and from the ski resorts.

Further, there was the World Economic Forum, at Davos, Switzerland; a one-percenter retreat. A few of the delegates may have, unknowingly, arrived with Covid. Following the Forum, many delegates – coming straight from a transmissible environment – will have visited the other hotspots for the rich and famous; the other alpine resorts, and the principalities Monaco, Liechtenstein, Andorra. And San Marino, which is a centre for the world’s semi-licit arms trade. All of these places had significant outbreaks of Covid19 during February and March 2020. These were perfect environments for the rapid spread of SARS-like coronaviruses. While coronaviruses are not winter viruses as such – compared to other cold and influenza viruses – they nevertheless thrive in winter when not obstructed by those other winter pathogens.

Essentially the most significant locations for amplifying Covid19 were greater-Milan, the Italian skifields centred on Cortina and Livigno; though Torino in the northwest – host of the 2006 Games – probably experienced its share of the unchecked Italian Covid19 flow. From these places it spread to neighbouring countries: Austria, Switzerland, France, and Bavaria in Germany.

Who else was there at those resorts? The managerial class – the bureaucrat and technocrat nine-percenters of the most affluent cities of northwest Europe, especially those cities hosting international (Geneva, Brussels, Luxembourg and Strasbourg) and national (eg Stockholm for one; and Paris and Berlin of course) governance organisations – were there with their older children. Fly-in, fly-out; a week’s break from the office with the family. In many cases parents on their own with the children while their spouses and ex-spouses enjoyed time apart from their children; elite parents and teenagers who would take the opportunities to socialise during the long après-ski evenings. They would mostly be back in their home countries by the first week of March.

Visitors from the Americas – from those same socio-business milieux – would have also been in these resorts at that time, and also in the capital cities of western Europe.

Covid19 didn’t stream into New York from China or from Seattle. It streamed in from the affluent centres of and close to alpine Europe, and from the business and political capitals of northwest Europe. Covid19 came into the Americas directly or indirectly from Italy to a much greater extent than it came from anywhere else.

Missing Maps

What was needed was good flow maps, much like those devised by John Snow, in London around 1850, to chart the cholera epidemics of 1849 and 1854. Instead, the statistics most available were nationally-compiled accumulations of cases and deaths; not international flow maps showing the sequences as Covid19 moved from some places and then on to other places. Individual countries were making their own imperfect maps, with their own make-believe boundary walls. In reality these European borders were for administrative purposes only. Herein lay the problem of visualising the flows of infection; unjoined maps. Further, these case-maps were often unadjusted for the population sizes of each country or province; many maps simply showed that there were cases where there were more people.

For flow maps, you must remove the dots which represent cases resolved by time or, for a small minority of cases, by death. And you must provide per capita data.

These administrators literally failed to join the dots between their own patches and their neighbours’ patches. A glance at any Europe-wide case-map would have shown, by April 2020, a large cluster of cases from Geneva north towards Strasbourg and Luxembourg, and then west towards Maastricht and Brussels; this cluster straddled six separate national borders. (Seven countries if you include Italy, which is close to Geneva.) The conclusions from such a map would have been as obvious as those revealed by John Snow’s case-map of Soho (London) during the 1854 cholera outbreak there.

In early 2020, it was senior public servants, their families including their elderly parents, their staff, and the people they had meetings (and eatings) with who had been most effectively spreading and succumbing to the virus.

First and Second Waves

By July 2020, the Covid19 outbreak was largely contained in Europe. But at a cost, not only in terms of disrupted income-earning opportunities to the small-medium businesses personnel who contracted the virus from the holidaying returnees and who were most disrupted by stay-at-home orders. And also, the latent cost of the first wave included the loss of those many natural immunisations that commuters in large cities experience most days of their working lives; especially cities with international airports.

Thus, the countries which had experienced multi-month shutdowns rebuffed the pandemic virus at a significant hidden cost; a weakening of the immunity of the population, increasing the susceptibility of the so-far uninfected to a new wave of respiratory contagion. Populations in urban centres – historically, and especially immigrants to those cities from the provinces – have always been vulnerable to transmissible diseases. By August 2020 this was especially so, especially in those countries in Eastern Europe (with older and poorer populations) which had been minimally exposed to both the first wave of Covid19 and the other pathogens they would normally have come into frequent contact with.

While the pandemic was contained in Europe by July 2020, it was far from contained in the United States. In the United States, the covid curve was flattened, but at a high plateau. The downside of flattening-the-curve is that you get an extended curve, creating a pathogen reservoir for a second wave of infections.

The Grand Tour and the second wave of Covid19

In the eighteenth century, a time of very high economic inequality in the British Isles and other parts of Europe, a tradition developed among the sons of the then one-percenters to do a Grand Tour. For a few, that tour was somewhat intrepid; Joseph Banks did his grand tour on the Endeavour with James Cook. Lord Byron was another, whose tour was somewhat intrepid and was never completed.

For the majority of these entitled young men, there was a tourist trail that developed; the grand tour became a kind of hedonist pilgrimage. Principal stops included Paris, the Rhine lands (including Heidelburg) and Switzerland. Some of these early bohemian tourists headed directly from Switzerland to Italy; others ventured into Austria (especially Vienna) and the Bohemian capital of Prague.

In Italy there were several must-visit cities, including Milan, Venice, Florence, Rome and Naples. The homeward journey likely included Sicily, southern France and places in Spain and Portugal.

Some grand tourists would also visit the ‘Near East’, the areas – including the Holy Land – defined by the Aegean and Eastern Mediterranean Seas.

The twenty-first (and late twentieth century) version of the grand tour is undertaken by the sons and daughters of American ten-percenters. In the United States in particular, working-life career-building requirements and surprisingly little annual leave strongly encourage this somewhat-elitist comparator to New Zealand’s OE. Young Americans have much less time than young Europeans to travel as tourists during their working lives.

In the modern Grand Tour, which lasts from mid-July to mid-September, young university-educated Americans with both left-elite (nine-percenter) and right-elite (one-percenter) backgrounds descend upon Europe. In 2020, this timing coincided with the re-opening of Europe after what the Europeans optimistically presumed was the end of the Covid19 pandemic. Further, European tourist hotspots were keen to welcome new waves of spending visitors, to help with their economic recoveries.

The second wave of the Covid19 pandemic began in August 2020, though this was not fully apparent until late September. The second wave was much more lethal than the first, and especially in Eastern Europe, where the (generally older) populations had largely escaped the first wave, but were particularly immunity-compromised as a result of the stay-at-home orders during the pandemic’s first wave.

The second wave began in places like Amsterdam, Paris, Barcelona, Switzerland, Czechia (especially Prague). And in Israel, another popular destination for American grand tourists. It was the American Grand Tour which brought the pandemic back to Europe, and with a vengeance; and which in turn instigated the further lethal waves of Covid19 around the world in 2021.

Unfortunately, thanks to inadequate specific-location-mapping and flow-mapping of the abundant Covid19 statistics, this flow of infections was only apparent to those who looked under the bonnet. By then, the national Wikipedia sites for Covid19 had lost their energy, showing increasingly outdated maps, and misplaced emphases on first-entry cases during the first wave. The accessible information was either too technical or too stale.

Popular Lore

In popular lore, the Covid19 pandemic was essentially a 2020 phenomenon. TV dramas and documentaries still emphasise that early period of the global crisis.

It was from the lethal second wave that the nasty new variants evolved, in 2021; and spread into and then from India, as the most spectacular example. Remember the Greek Alphabet soup, with the (British) Alpha and (Indian) Delta variants having been especially problematic.

The older Swedish scientists who emphasised the need to take a path – a path which accentuated the need for natural immunity to facilitate an early and complete end to the pandemic’s most dangerous phase – were proved correct as the pandemic raged through its most serious phase in 2021. Though you wouldn’t know it, probably too many interests did not want to make comparisons. Sweden’s politicians had been too slow to address the Stockholm outbreak in early 2020, when that country had an especially vulnerable elderly population; so, it looked as if the world had little to learn from that country. (Sweden had had significantly less influenza than most other countries, in 2018 and 2019; meaning that Sweden had unusually low death rates in the winters of those two years; meaning that they had plenty of ‘fuel’ for a tragic pandemic ‘fire’ in the spring of 2020.)

2021 also became the year of the Covid19 vaccine race; whereas 2020 had been the year of the missing PPE. The public health industry tends to place too much emphasis on immunisation through intervention versus immunisation through monitored natural exposures. This emphasis is valid for the most lethal of infectious conditions; the conditions for which we routinely vaccinate today. But for the below the radar circumstances of categories of common respiratory viruses with high complexity and low lethality – including known circulating viruses such as RSV, coronaviruses (the descendants of previous lethal coronaviruses), rhinoviruses, and influenzas –medicalised immunisations came to be emphasised while, with little awareness, simultaneous processes were lessening immunity to these types of virus. It was like taking one step forward and two steps back.

In the end, the pandemic was resolved through a natural immunisation process. 2022 was the year of Omicron. In 2022 the non-lethal Covid-Omicron variant ‘ripped through’ New Zealand and other places with previous minimal coronavirus exposure. This was a direct result of the failure and subsequent redundancy of the border-quarantine and other barrier methods of protection which were still in force in January 2022. Most New Zealand residents were exposed to covid that year.

Omicron had evolved in southern Africa in late 2021, from the earliest strain of Sars-Cov2. It became a natural immunisation force. Omicron was the invisible cavalry coming to the rescue; favoured in evolutionary terms over the Delta nemesis because it was more highly transmissible while being much less lethal than the previous covid varieties. More like the familiar but under-studied ‘common cold’ coronaviruses. Omicron stopped Delta dead in its tracks; a more effective weapon than the Pfizer and Moderna vaccines.

Lessons

I don’t think that western society has learned very much from the Covid19 pandemic. The importance of good mapwork and monitored natural immunisation barely formed any part of the long but largely useless narrative. Sweden’s alternative scientific path was forgotten, or derided, rather than learned from.

The next pandemic will probably also catch us unawares. It will be as different from the contemporary preoccupations of epidemiology, as Covid19 was. It may already be ‘hiding in plain sight’, as the coronavirus threat was in the 2010s. Family doctors should be routinely testing for all the various ‘bugs’ out there, and passing-on data about the various pathogens and cross-immunities which keep us healthy in daily life. We could perhaps have knocked out Covid19 in its early stages, by facilitating natural exposures of healthy people to low doses of already-circulating non-covid coronaviruses.

I think that future government-overreach mandates around lockdowns and mask-wearing will be hard to enforce, given the huge rightwards shifts in western politics this decade. But there may be opportunities for short smart protective measures, undertaken at local levels and in places such as retirement villages and rest homes. In particular, making high-grade (ie the more expensive types of) facemasks available to the vulnerable, with the warning that these should be worn mainly in high-risk environments, and not everywhere all the time.

Meanwhile

It’s great that Milan and Cortina d’Ampezzo, still popular hangouts of the rich and the not-so-famous, have been able to host a magnificent sporting event. These places have not been tainted by their association with the still recent pandemic. Despite being the places from which an outbreak of a significant new coronavirus fanned out to create a three-year pandemic that changed the world. That outbreak was probably containable, if we had acted with more nous and more knowledge of the common pathogens of daily life.

But who was looking at the Italian Alps in those heady ski-holiday days of February 2020? We were transfixed by China.

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Keith Rankin (keith at rankin dot nz), trained as an economic historian, is a retired lecturer in Economics and Statistics. He lives in Auckland, New Zealand.

On Monday morning on RNZ’s Morning Report, Revenue Minister Simon Watts admitted that it was a legitimate option for ‘landlords’ to leave their houses empty. (Refer Revenue Minister on mortgage tax deductions for landlords, RNZ 11 March 2024.) The official narrative of the elite political class is that when tenancies on rental properties end, the houses are retenanted or sold; sold either to an owner-occupier or to a landlord who lets the property to new tenants. They don’t usually admit to owning homes which are fully or substantially empty.

I might also mention that, in one of the leaders’ political debates before the 2023 election, both Chris Hipkins and Christopher Luxon were asked a question about whether they favoured a tax on owners of empty houses. Both leaders appeared discomforted, as if this was a naughty question that should not have been asked, and then recombobulated themselves by saying ‘no’; a response that was to be expected from Luxon, but which may have cost Hipkins a significant number of votes. (In addition to not including such an obvious policy in the Labour manifesto, Hipkins’ cold rejection of an empty-house tax revealed that Luxon is not our only tone-deaf political leader.) Clearly neither leader had been briefed on the issue, despite such taxes being adopted overseas and despite the policy idea circulating widely in the New Zealand non-mainstream media.

An additional feature of the Simon Watts interview was the Minister’s defensiveness towards Corin Dann’s use of the term “property speculator”. When Dann pressed Watts on the matter, Watts was unable to deny that some so-called ‘investors’ were indeed ‘speculators’, and sought to fudge the issue by saying that typical ‘landlords’ are ‘ma and pa investors’ with just one or two rentals (presumably in addition to their ‘ma and pa family home’. This seems at odds with his earlier admission that professional investors have a valid option to leave rental properties untenanted; because the popular image of ‘ma and pa’ landlords is of people housing tenants who they know and have a relationship with, not an image of ruthless speculators.

It is worth reminding ourselves about maverick economist Gareth Morgan’s 2017 comments about residential landlords: see A hard look at Gareth Morgan’s plan to save New Zealand’s renters, Madeleine Holden, The Spinoff, 9 August 2017. Quote from Morgan: ‘”Look at me, I own six houses, ” he stated on The Nation. “I don’t have tenants; they just make carpets dirty. I do it because I know you [other investors] want to get in on this as well, and so you’re going to bid the price of those houses up.”‘

Leverage: how it works to create speculator paradise

Ruthless property speculators – of which there were many from 2003 to 2008 and again from 2011 to 2017 – use the principle of financial leverage to get a return principally from capital gain. (Capital gains taxes in other countries did not stop this process.)

The context is that New Zealand’s housing crisis is principally one of market and government failure in private rental housing. And we should note that this failure is less an Auckland problem and more a problem of New Zealand’s provincial cities and towns, and Wellington. Additionally, it is a crisis of urban land prices, and – as in the later 2000s – a crisis aggravated by high interest rates. Into this mix we face a change to taxation which will aggravate rather than diminish the housing crisis.

The principle of financial leverage works like this. Mr S has a million dollars and wants to double his money in two years. He has been told by his financial adviser that residential property is appreciating in price by ten percent a year. Further a typical house costs one million dollars. Mr S buys five houses with his million dollars; that $200,000 per house of his own money. He borrows the remaining four million dollars. (He may then list his houses on Airbnb, as ‘short-term’ rentals; he may even let his properties to genuine tenants, or he may leave them empty.) In two years time he expects to sell all five houses for 1.2 million dollars; that’s six million dollars in total. After repaying his mortgages in full, he would get to keep two million dollars. That’s a doubling of his initial outlay of one million. (OK, there will be some expenses; nevertheless Mr S expects to be smiling all the way to the bank when he realises his near 100% capital gain over two years.

Mr S is an example of a leveraged landlord. And he will make even more money if he doesn’t have to pay tax on his mortgage interest ‘costs’. But not all landlords are that highly leveraged. Some are not leveraged at all; they are letting mortgage-free properties to tenants. These landlords cannot gain from the deduction of tax for mortgage interest costs. So, in the coming years, they will not charge lower rents on account of lower costs. And it is these unleveraged landlords who will set the market price for private residential rental houses. (And many of these price-setting landlords will be ‘ma and pa investors’ approaching retirement age.) The leveraged landlords, if actually renting out their properties, when setting rents will take their cue from the unleveraged landlords; therefore, they will accept the reinstated tax deductions as windfall profits.

Rents will be at whatever price the market will bear, and not discounted by individual landlords with falling tax costs.

Auckland Regional Fuel Tax

Something similar will most likely happen with the repeal of the Auckland regional fuel tax. At present with the regional fuel tax in place, petrol prices in Auckland are not much different from the rest of the country. That wider nationwide price will tend to be the main determinant of ongoing petrol prices in Auckland, meaning the petrol retailers will gain a windfall when the tax ends. Auckland petrol consumers will gain less than what Mobil and BP will keep.

More generally, we see a pattern from this government to replace proportional taxes with regressive charges; for example, favouring increased car-registration fees over fuel taxes. The cost burdens are increasingly placed on those least able to afford the costs. (This situation can also occur if fixed charges for water or electricity increase faster than usage charges.)

House Prices

The granting of a licence to speculate is likely to set-up the next round of residential property price appreciation. (My sense is that other global economic headwinds will limit the next property bandwagon to no more than three years.) The issue today is much as it was in 2005, with the downturn in the tradable economy, caused in large part by higher interest rates, pushing bank lending into the non-tradable economy, especially property.

Lending to the property sector is less sensitive to interest rates than lending to businesses which export or compete with imports. The New Zealand economy is now primed for a shift in lending towards the property sector. In addition, consumer lending will likely stay strong; this will be driven more by the budget shortfalls of financially stretched households than by interest rates; consumer lending is largely interest-insensitive.

As house prices rise, rents can be expected to rise as landlords – unleveraged and leveraged – seek to maintain their percentage yields on capital. Let’s say that the expectation is that a $500,000 house in the provinces is expected to yield a rent of $500 per week; landlords’ expectations would be that if the $500,000 house becomes a $600,000 house then it should earn a rent of $600 per week. (In reality, in times of property price booms but little employment growth, there is quite a lag in rent increases; renters are simply unable to pay such proportional rent increases.)

What is likely to happen in the next few years – when the speculator community has its mojo back following the removal of tax on mortgage interest – is rents increasing faster than they otherwise would.

‘Investors’ owning just one home.

There is one class of landlords who require special attention. This is people who own just one home, which they rent out to tenants, while themselves renting their own dwelling.

I was in this situation from 2009 to 2014, having received an inheritance a few months after moving into a rental house which particularly suited my family’s circumstances. Other people will be in this situation if they move out of their family home to accept employment in another city. And other people, wanting to own some property as a hedge against poverty, will want to buy a cheapish rental in another town or an outer suburb; yet will themselves want to keep renting closer to where they work or to where their children go to school.

These people should pay zero tax on their rental income if the rent that they pay is more than the rent which they earn. While there is a case to treat mortgage interest as a legitimate ‘business’ cost for property owners, if the rent they pay offsets the rent they earn, then the question should not arise; there is no income to tax. So the critical reform here, that the National Party should be leading the way on, is to deduct rent paid from rent earned. More generally, these ‘landlords’ – who own just one property – should be treated more as owner-occupiers than as investor businesses.

Fiscal Austerity? Despite tax repeals.

We are being promised public austerity alongside the tax repeals which foster increased private affluence for a few. Tougher times stifle the circular flows that underpin a prosperous economy; austerity begets more austerity in a downward spiral, until someone finally rediscovers Keynesian economics.

Cabinet Minister Tama Potaka unashamedly advocated “austerity” last week, on Newshub’s AM show (1 March 2024): see ‘Not a free ATM card’: Taxpayers won’t bear cost of saving Newshub, minister says | AM. (The ‘austerity’ quote comes 8’38” into the video-recording. Lloyd Burr, the interviewer, looks genuinely surprised at this candid admission.)

In relation to Potaka’s comment we have this on Newshub on 5 March 2024: Finance Minister Nicola Willis rules out increasing GST after Labour speculation. The web-story discusses public austerity in the light of Potaka’s comments. This interview was a response to Why Labour’s new finance spokesperson Barbara Edmonds thinks a tax hike could be on the cards on Newshub the day before. Nicola Willis knows better than Tama Potaka to avoid the ‘austerity’ word. But Nicola Willis is showing all the signs that she will be like her 1990s’ predecessor Ruth Richardson, who cut benefits and became Aotearoa New Zealand’s exemplar for fiscal austerity following her “mother of all budgets”.

Finally, Two questions for Christopher Luxon:

Prime Minister Christopher Luxon owns four investment properties as well as three residences.

Question: Are you a good landlord, Mr Luxon?

Supplementary Question: How many of your four investment properties are currently tenanted?

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Keith Rankin (keith at rankin dot nz), trained as an economic historian, is a retired lecturer in Economics and Statistics. He lives in Auckland, New Zealand.

In the European Union at least, mortality data is now available until close to the end of 2023. In northern Europe, mortality has been markedly higher than it should have been in the ‘Fall’ – autumn – of 2023. The main exception is Poland. Respiratory illness is most likely the culprit.

My working hypothesis is that excess deaths since mid-2021 have been mainly due to reduced immunity – general and covid specific – and that the extent of deficient immunity is largely a function of the duration of ‘public health’ lockdowns and facemask mandates. Other contributing factors would be the severity of the viruses in circulation, and the numbers of people vulnerable due to age or pre-infective morbidity.

Finland seems to have been hit particularly hard and early, this autumn. The deaths suggest an outbreak of Covid19 or something else towards the end of September. Finland fits the working hypothesis, with little sign of a Covid19 impact until mid-2021, and then a consistent pattern of excess deaths. Finland’s population is looking distinctly unhealthy, and with no evidence yet that 2024 will be much better. Finland had probably the strictest public health barrier mandates (lockdowns and facemasks) of all the Scandinavian countries.

Sweden is the opposite of Finland, with substantial excess mortality in 2020 and January 2021. From February 2021, Sweden’s mortality has looked normal. There were 2022 mortality waves synchronous with Finland, but smaller and briefer (except December 2022 which was high throughout Europe). Sweden has caught the autumn 2023 wave, but later and not as seriously as Finland. We’ll watch to see if there was a mortality fall-off there in December. (We note Sweden had a particularly benign 2019, meaning that it had in 2020 a group of older people who would have died in 2019 had 2019 been a normal year.)

Germany looks much like Finland, except that it experienced the winter 2020/21 wave which Finland avoided due to its public health restrictions. Germany experienced a ‘spiral of death’ in the second half of 2022. While most of 2023 has been about normal in Germany, the autumn mortality wave was serious and possibly ongoing. Germany is a country with weakened immunity, at least according to my hypothesis (given its extensive and prolonged public health barrier mandates), and which seems to have been exposed to the worst of whatever viruses – or virus strains – have been circulating recently.

Poland appears to be an enigma, though it does fit my working hypothesis. Poland showed no significant Covid19 mortality until September/October 2020. Like other Eastern European countries, it suffered twice as much as Western Europe in the winter of 2020/21. This, I have hypothesised, is due to the substantially weakened levels of general immunity in East Europe in the fall of 2020. Poland also suffered severely from waves of Covid19 in the spring of 2021 and the winter of 2021/22. Then, in 2022, Omicron Covid19 seems to have acted as a natural vaccination, making its experience much less severe than the experiences of Germany and Finland. 2023 looks to have been particularly benign in Poland.

We should note that Poland’s elderly took a hammering in 2020 and especially 2021, so there were fewer of them in 2022 and 2023. But, all of Eastern Europe has an older population, especially of postwar baby-boomers, in large part because the has been a westward drain of younger people. Poland’s population remains ‘oldish’, despite the demographic ‘haircut’ faced by that country in 2021. It’s population now looks remarkably healthy; presumably with high restored levels of general immunity.

(Another problematic country of North Europe, not shown here, is Ireland. Ireland imposed greater public health restrictions than the United Kingdom, but, like Finland, has had a distinctly queasy time of it since July 2021. Before the British pillory their government too much over its Covid19 public health response, a good comparative analysis, looking at all four years from 2020 to 2023, might suggest that the excess mortality data in the United Kingdom may not have been much better had they adopted a different set of public health policies.)

For interest, I have added charts for Greece and South Korea.

Greece got Covid19 late, and had a bad 2021, though not as bad as Poland. Early 2022 was worse in Greece though. We also note that Greece is unusual, because it has substantial summer death waves. Most of this will be due to the numbers of people passing through Greece, in the context that its visitor-to-local population ratio is unusually high each summer. Then, in 2022 and 2023 there were the big wildfires, which also contributed to excess mortality. There is no sign of excess mortality in Greece this autumn. It may not have received much of the virus infectivity that has been apparent in the north. Or, Greeks may have better restored their levels of general immunity than have Finns and Germans.

Finally, South Korea has this remarkable picture of having been little affected by Covid19 – at least in the death data – from March 2020 until July 2021. (It did have a significant early outbreak, in February 2020.) Things started to go wrong in Korea after July 2021, followed by a fullscale deathwave from February to April 2022. This was the less-severe Omicron variant, so clearly the Korean population was not prepared; Koreans must have had very low natural and vaccination immunity, owing to excessive and prolonged facemask wearing (and an insufficiency of vaccination boosters). Further, South Korea has had significant excess deaths since August 2022. It’s too early to say how the northern hemisphere autumn wave has affected South Korea; that country is tardy in releasing its data.

For the most part the data fits my working hypothesis, although Sweden is starting to converge more with its Nordic neighbours, all of which followed more restrictive policies. Sweden continues to have large numbers of very old people, reflective of its early exit from the Great Depression and its neutrality in World War Two.

(And, just an aside, it’s remarkable how many very old people are still alive in Japan, given its World War Two experience. Indeed I have visited the Nagasaki Atomic Bomb Museum, which I thought gave a very fair representation of the events of the war in Japan. And I visited the ‘ground zero’ Hypocenter Park. Sobering. Many Japanese will have survived due to the lack of a protracted ground war in that country. Korea, on the other hand, has a demographic structure significantly more determined by both World War Two and the active historical phase of the Korean War. South Korea’s excess mortality might have been substantially greater had it had a full quota of octogenarians and nonagenarians.)

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Keith Rankin (keith at rankin dot nz), trained as an economic historian, is a retired lecturer in Economics and Statistics. He lives in Auckland, New Zealand.

Analysis by Keith Rankin.

This chart shows total deaths in a number of comparable countries with high or highish life expectancies. The countries with most deaths have older populations.

New Zealand should perhaps be compared most with Ireland, Scotland, Denmark and Finland; all countries with just over five million people. And with Australia.

Australian mortality has been similar to New Zealand’s in recent years, though, as more New Zealand citizens migrate to Australia, in the next few years New Zealand will age faster than Australia.

Ireland is exceptional because of its relationship with United States’ high technology companies and its full membership of the European Union. Thus Ireland has many elite ‘tech’ workers at present. Further, in past years of difficulty – especially 2008 to 2014 – Ireland was able to unload much of its underclass to other countries. While the health and financial circumstances of Ireland’s sixty- and seventy-somethings requires further investigation, Ireland will neither have had as big a baby bust as New Zealand in the 1930s nor as intense a baby boom from 1946 to 1965. So, it is likely that the numbers of deaths in New Zealand will rise faster in coming years than the number of deaths in Ireland.

The high death numbers in Scotland, Denmark and Finland do not reflect lower life expectancies in those countries. Rather, they reflect populations with comparatively fewer younger people compared to older people. These countries’ mortality numbers in 2018-2022 are the best guide we have to what death numbers will be like in New Zealand in coming years, as the baby bust generation passes on and the 1940s’ and 1950s’ baby boomers reach the days in which they dominate death data.

Most importantly, the experience of these three countries suggests that we will see the demand for health care in New Zealand surge from now on – peaking in the 2030s and 2040s – at a time when current projections show that New Zealand’s healthcare workforce will trough. There seems to have been minimal, if any, demographic analysis of the implication in New Zealand of a baby bust generation giving way to baby boom generations. This is despite record numbers of policy analysts and cost analysts contracted by government.

Some Particular Comments about other countries

I have included Qatar and its near-neighbour Oman to show how low death numbers are at present in small Arabian countries with relatively large numbers of working-age residents. I think that this observation also applies to Israel.

We note also the death incidence in the higher life expectancy countries of Latin America – Costa Rica, Colombia and Chile – on account of their relatively low numbers of people in their eighties.

We note that Portugal and Japan have relatively high numbers of elderly people in their populations. Portugal has been a retirement magnet within Europe, with strong links to the United Kingdom. I have generally been puzzled as to why Japan has so many older people, though we should note that the generation which fought in World War II has largely passed on. I guess that, as in England, many Japanese children in the war were transported into the countryside so that they were not in the cities which suffered very intense bombing from the United States. Overall, Japan is one of the most age imbalanced countries; the low birth rates in recent decades contribute most to this.

Germany is a country which suffered particularly from Covid19 and similar diseases in 2022. But its high 2018 death tally suggests demographic causes which still need unravelling. Despite Germany being a major labour inflow country in Europe, it still has a median age about ten years higher than New Zealand’s (47 compared to 37).

On the flipside of Germany’s role as a labour-inflow country within the European Union, we have Finland and the other Baltic states as outflow countries. Hence the high death tallies in Finland and the Baltics relative to their resident populations.

Neither Finland nor Denmark look particularly happy in this chart. I predict that New Zealand’s death tally will soon be like Finland’s, given both countries’ propensities to lose labour to bigger neighbours. The situation of Greece is similar to that of the Baltic counties; too great a loss of their younger people to the employment centres of the European Union.

Re a few countries not in the chart, I can affirm that both England and Netherlands have population-adjusted death tallies very similar to the United States. And Canada’s adjusted numbers are very similar to Norway’s.

Finally, we should note Sweden, which was neutral in World War II. So Sweden does not have the extreme demographics of older people which New Zealand and other war participant countries exhibit. And, Sweden was less impacted by Covid19.

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Keith Rankin (keith at rankin dot nz), trained as an economic historian, is a retired lecturer in Economics and Statistics. He lives in Auckland, New Zealand.

Fresh vegetables and fruit – quality foods – are what economists call a merit good, like primary health care, education and urban public transport. By contrast, ‘junk food’ – rich in sugar – is a demerit good. We in New Zealand and many other countries have a problem: too much unhealthy junk food is consumed, and too few quality foods are eaten.

Economics 101 has a simple textbook solution which I am sure all economists would agree with. To encourage increased consumption of vegetables and fruit, these foods should be subsidised. Just as we subsidise the other merit goods mentioned above.

We should note that subsidies incentivise production as well as consumption. Indeed it is entirely beneficial to society for such a subsidy to benefit market gardeners, orchardists and greengrocers (ie not only consumers). In particular, such a subsidy might have an impact on land use; a significant part of the ‘cost of living’ problem we face is the loss of good horticultural land close to our cities.

We could set a rate of subsidy at 15 percent, knowing that if the policy achieves its goals of incentivising consumption and production of fresh and unprocessed horticultural products, then there would be a future option to increase the rate of subsidy.

Instead of such an obvious and simple policy, we are having a restricted debate about a convoluted and inefficient ‘tax cut’. As an economist – albeit a retired economist – I agree with the professional consensus that the Labour Party’s tax policy is inefficient and regressive. Nevertheless, I found this item on RNZ this morning somewhat problematic: Tax experts slam GST-free fruit and vegetables policy.

The college of economists interviewed have downplayed the central ‘merit good’ issue. They emphasise the ‘income effect’ over the ‘substitution effect’, whereas tax specialists in the past have generally emphasised the ‘substitution effect’ over the ‘income effect’, especially with respect to labour supply. (This is manifest by their emphasis on marginal tax rates over average tax rates.) And they seem to think that the only suppliers of note of vegetables and fruits are supermarkets, who they insinuate will suddenly become even more greedy than they allegedly already are. They are being disingenuous. Most problematic was the suggestion by one of these ‘leading’ economists – a popular label used by much of the media applied to the people they talk to – that an economist who breaks rank from groupthink does not deserve to be called an economist.

Labour’s reasons for not subsidising vegetables and fruit are, at first sight, quite puzzling. But we must remember that party policy is discussed in a political context, and that groups of like-minded people in a committee tend to advocate partial rather than imaginative solutions. (While subsidising vegetables and fruits is hardly an imaginative solution, nevertheless almost nobody seems to have imagined it!) My guess is that the bigger reason why Labour have chosen their GST-meddling ‘tax’ policy is that it is needed as a fig-leaf to mask their absence of a tax policy.

Subsidise unprocessed vegetables and fruit! Such an incentivisation policy would be popular with both the public and the economists. Good economics and good politics.

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Keith Rankin (keith at rankin dot nz), trained as an economic historian, is a retired lecturer in Economics and Statistics. He lives in Auckland, New Zealand.

Analysis by Keith Rankin.

These three countries are very useful comparators because they have broadly similar demographics – especially population age structures – to each other. Further they have comparable living standards. The Republic of Ireland has a population the same size as New Zealand (and a similar climate); Australia has close to five times the population of each of the others.

Of the above charts, Ireland best shows the three main waves of mortality in the Covid19 Pandemic. [Note that I will capitalise the word ‘pandemic’ for a WHO-declared pandemic. Otherwise uncapitalised.] There are very clear covid mortality peaks in Ireland in April 2020, January 2021, and December 2022. Other than these peaks there are clear periods of elevated mortality, the second half of 2021 and most of 2022. 2023 also, from March.

Ireland’s population has been growing more slowly this century than Australia’s and New Zealand’s. Death tallies before the Pandemic years were not noticeably growing from 2015 to 2019; compare Australia below. There was an influenza pandemic from late 2016 to about April 2018; the high numbers of deaths in Ireland in January 2017 and December 2017 reflect this. (I have omitted 2016 and 2018 to avoid chart clutter. For Ireland, influenza pandemic deaths actually peaked in January 2018, and extended into March of that year.)

The most obvious difference in the New Zealand chart is the southern hemisphere seasons. The second most obvious difference in New Zealand is the lack of obvious Covid19 waves.

The scales of the two charts are fully comparable, because of the near-identical populations of each country. But a careful look will show that ‘normal’ – ie baseline – summer deaths in Ireland are lower than in New Zealand. Ireland’s population may have better baseline health than New Zealand’s. Or, New Zealand may have more deaths because it has a higher population of post-war ‘baby-boomers’ than Ireland; a population which is now starting to die in greater numbers.

The New Zealand data are worrying in other ways, however. While 2017 clearly shows the 2016-2018 influenza pandemic, with its July 2017 mortality peak, summer data for 2017 and 2019 don’t show large increases in deaths arising from population growth. The period from March to July 2019, in the absence of known epidemic illness, nevertheless looks like a protracted period of deaths triggered by early seasonal viruses. (Indeed, I recall from my former workplace that there were a lot of ‘bugs’ around for parts of 2019.)

If we regard the April to June periods in 2017 and 2019 as having elevated death tallies, then 2021 looks like a normal year in New Zealand, even allowing for population growth. Yet it wasn’t a normal year. It was the peak year of the Covid19 panic; the year of the most extreme public health mandates, with an effectively shut international border and with face-masking required in many settings. The big question is to ask why 2021 was not more like 2020. In the winter of 2021, New Zealand had no Covid19 to speak of, and no influenza.

Elevated death tallies reappeared in March 2022, continuing through to January 2023. While these were clearly linked to Covid19, there was no mortality peak anything like that which Ireland experienced in December that year. My guess is that the timing of mortality in New Zealand reflected the timing of booster vaccinations against Covid19, whereas Ireland was caught unawares that December.

A good check on these tentative conclusions for New Zealand is Australia. (The scale is five times higher, reflecting that Australia’s population is five times greater.) Australia shows most of the same features as New Zealand in the years before 2020, though in a muted way. Australia shows more consistently than New Zealand the impact of population growth before 2020 being reflected in more deaths each year than the previous year. We see that in the spring months (September to November) Australian deaths are generally lower than New Zealand’s; probably because winter lingers for longer in New Zealand.

Australia shows the same problem in 2021 as New Zealand; normal winter deaths despite highly abnormal circumstances. As in New Zealand, there almost certainly were ‘killer viruses’ in both countries that year. Deaths to some extent will have been people who would otherwise have died in 2020, but avoided viruses then because of the lockdowns and physical distancing. Also, weakened immunity arising from the lack of normal exposure to respiratory viruses in 2020 will have increased the chances of vulnerable people dying in 2021 after contracting such a cold virus. The 2021 mortality peaks were higher in New Zealand than in Australia.

Australia shows a classic Covid19 mortality peak in January 2022, before the ‘Omicron’ variant of Covid19 was discovered in New Zealand. Australia had covid exposure peaks in December 2021, much of that being the Delta variant, pre-Omicron. In the autumn and early winter of 2022, Australian mortality data show a shorter and lower ‘Omicron wave’ than New Zealand data.

All three countries continue to show elevated levels of mortality this year, though this is obscured in New Zealand by the problematic numbers of deaths in the autumns and early winters of 2017 and 2019. New Zealanders in the first four months of this year have had slightly more deaths (adjusting for population) than Australians. This may reflect New Zealand’s relatively more overstretched healthcare system, noting from having myself spent some time in Australia this year that Australians also see their healthcare system as overstretched.

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Keith Rankin (keith at rankin dot nz), trained as an economic historian, is a retired lecturer in Economics and Statistics. He lives in Auckland, New Zealand.

The Pandemic can be assessed a bit like games of football, with deaths being the score. (Or, given that there are many ‘teams’ competing together, a better analogy may be a Marathon race. Nevertheless, I will use the language of the football metaphor.)

The winning country would be that with the fewest number of deaths attributable to Covid19. While this football metaphor is indeed useful, our perceptions of ‘who did best’ are strongly coloured by the pandemic’s first year, when media attention was greatest, when public health measures were most ‘in our faces’, and when the pandemic response was at its most bureaucratic.

As a result, the half-time scores are the scores that most seeped into public consciousness. Then, deaths which were classed as ‘covid-deaths’ were implicitly seen as more tragic, more requiring of daily tallying, than other deaths.

The two Tables below look at this Pandemic ‘World Cup’ through the simple demographic criteria of increases in deaths, all deaths. We may note four ‘ordinary-time’ phases of the pandemic. Together, they add up to a period of four years.

First, the warm-up, from May 2019 to February 2020. The warm-up, going back to 2019, is important to include because countries with unusually low numbers of deaths due to respiratory illnesses in 2019 would typically have higher death tallies in the next respiratory epidemic, whatever virus that might be.

Second is the first half of the Pandemic proper, which I would date as March 2020 to March 2021. Third is the second half, from April 2021 to April 2022, which includes the waves associated with the Greek-alphabet variants (especially Alpha, Delta and Omicron).

Following ‘ordinary-time’, there was ‘extra-time’ which I define as May 2022 to April 2023. We may note that the WHO declared the Pandemic to be over at around the end of April this year. So, we may formally categorise the period from May 2023 as ‘post-pandemic’.

Table 1 below indicates the score at the end of ordinary-time. It shows the percentage increase in deaths for a number of countries for the three years from May 2019 to April 2022, compared to the three years from May 2015 to April 2018. In the right-hand column is a counterfactual which is a best estimate of what the increase in deaths would have been in the pandemic period had there been no pandemic. (The counterfactual is calculated by comparing deaths in the 24 months ending April 2019 with deaths in the 24 months ending April 2017. I have used April years because, in both hemispheres, the period in late April and early May is generally free from epidemic respiratory deaths. This method minimises the impact to this calculation of the severe influenza global epidemic which lasted from late 2016 to early 2018.)

Table 2 indicates the ‘extra-time score’, comparing the year-to-April 2023 with the year-to-April 2019. It uses the same ‘trend’ counterfactual as Table 1. Whereas Table 1 is sorted to place the ordinary-time ‘winners’ at the top, Table 2 is sorted to place the ‘extra-time losers’ at the top. (We note that, for Table 2, some countries are laggards in publishing their mortality data; and also that the most recently published numbers are subject to upwards revision. The countries which are problematic in this regard have their data marked with asterisks, the number of asterisks indicating the degree of estimation required.)

In the pandemic proper, the two countries with easily the least increases in deaths were Norway and Sweden. The others in the ‘Top Eight’ (the ‘quarterfinalists’, to use the football metaphor) were the other Nordic countries, Australia and New Zealand, and Taiwan.

Based on the media coverage in New Zealand and the world news channels that New Zealanders mainly follow, the only surprise in that Top Eight would be Sweden, which pursued a very different policy response, especially in the ‘first-half’ of the Pandemic. In the 2020 New Zealand election campaign, political parties generally agreed that Taiwan was the exemplar for other countries to follow.

We may note that only New Zealand and Taiwan had counterfactuals showing higher projected increases in deaths than what actually happened. Thus, these two may be declared the ‘ordinary-time’ winners. The problem is that the Pandemic World Cup had ‘extra-time’. (It must also be noted, however, when we take the ‘non-death costs’ of the pandemic and its associated health policies, Sweden’s non-death costs were easily the lowest. So, on this basis, it could be argued that Sweden was the true ordinary-time winner, despite having been way behind at ‘half-time’.)

Extra-Time

When we look at Table 2 we see clearly that the East Asian countries performed very poorly. Most of these were deemed to be success stories in ordinary time. Taiwan is very prominent here. So is South Korea which has a conservative estimate in this table for its ‘extra-time’ increase in deaths. Macao is very important here, because it is the best proxy we have for China. Taiwan has had a recent resurgence in deaths in May 2023, and Macao has had a resurgence of Covid19 cases in recent weeks. So, these countries’ pandemic problems are far from over. (There are also signs that New Zealand’s seasonal death tally is picking up early this year.) The Macao situation, combined with other reports that all is not well in China right now, suggest that China may be presently going through a significant third wave of Covid19. This will add to global supply-chain problems.

New Zealand and Australia are in the top (ie worst) half of Table 2. So are two of the Nordic countries, Iceland and Finland, the Nordic countries which imposed more restrictive health mandates than their neighbours. So is Ireland near the worst, more restrictive in its public health mandates than the United Kingdom countries. Norway, top of Table 1, is in the middle of the Table 2 pack. Of the Nordic countries, only Sweden – easily the least restrictive in Europe, especially in the first-half of the Pandemic – performed well.

Quirky Counterfactuals

Creating consistent counterfactuals for each country is difficult because there are quirky demographics at play. First, we note that there are three main reasons why death increases might trend high for a given country. The first is a general increase in the population of a country: more people, more deaths. Second is the aging of a country, represented by increases in the median age of living persons. Third is a deterioration of general health, especially of those middle-age cohorts whose deaths ‘come under the radar’, given that deaths are dominated in most countries by people aged over 75.

It is likely that the high counterfactual for New Zealand is due to a mix of these. We know that New Zealand has some of the same issues of underclass deprivation as the United States, which include obesity, diabetes, and substance abuse. And we know that the United States has a lower life expectancy than other ‘western’ countries; a life expectancy now known to be falling.

The other two main quirks to look out for are birth rates in the troubled second quarter of the twentieth century. The Great Depression and World War Two were the main events that impacted on birth rates. There was also warfare in the 1950s in Korea and Malaysia. Sweden is an interesting case, comparable with Switzerland, neutral in World War Two, so having a lesser demographic impact from the War. Also, Sweden came out of the Great Depression early, meaning it will have had comparatively high birth numbers in the 1930s; Sweden’s peak deaths since 2015 will have been higher than otherwise, on that account.

While New Zealand is possibly the western country with the fastest population growth this century, this is offset by the fact that low birth numbers in the 1930s are translating to lower deaths since 2015. (See my recent ‘Smithometer’ analysis, in Granny Smith.) Aging and population growth are not the whole story of New Zealand’s upper quartile trend of increasing deaths. (Unlike, say Portugal, which is known to attract retirees in Europe as Florida does in the United States.)

New Zealand also has the additional factor of having, in June and July 2022, too many vulnerable people who were denied, for unexplained political reasons, a timely second booster Covid19 vaccination. The July 2002 mortality peak, almost entirely experienced by older European-ethnic New Zealanders – the Granny Smiths – came to a prompt end once these people became eligible for second-boosters. This sharp July peak – and drop-off – appears to have been a New Zealand specific phenomenon.

High counterfactual notwithstanding, New Zealand performed very poorly in extra-time, though not as badly as the East Asian countries which imposed the most ‘sterile’ public health policies on their people.

East Europe

I would like to note two other groups of countries. First, it was Eastern Europe which had the highest reported per-capita Covid19 death tolls. These countries do not look as bad in this analysis, though they (except the Baltic states) still look bad in Table 1, especially in light of their often negative counterfactual death trends. The main demographic problem that these countries have been facing is emigration of working-age adults, especially those Eastern European countries in the European Union. Generally, these countries look much better in Table 2, in extra-time.

Most of these countries successfully imposed severe public health restrictions in the first half of 2020, but abandoned those restrictions – or were unable to easily reimpose them – in the later stages of ‘the game’. The result was that these countries’ populations had substantially compromised immunity going into the winter of 2020/21. Their death peaks were much higher than the death peaks in the west earlier in 2020. The second problem was that, on account of their departed youth, their populations were aging as well as falling. Hence the high Covid19 per capita death tolls that savage winter.

In ‘extra time’, East Europe has ‘performed’ best. This would appear to be in part because so many of their most vulnerable people had already died; respiratory viruses had lost much of their human ‘fuel’. Also, these countries had re-established (the hard way) high levels of natural immunity to respiratory illnesses.

Russia continues to supply mortality data, though it excludes deaths in the Ukraine conflict zone; so its not included in the tables. And Ukraine has certainly stopped supplying data, due to governmental priorities as well as a lack of will to publicise its present demographic plight. Kazakhstan is probably the best proxy for assessing the impact of the Pandemic in Russia.

South America

These countries (plus Mexico) are among the worst performers in both Tables. Typically, they exhibit many of the ‘underclass’ socio-economic problems apparent in the United States, United Kingdom, and New Zealand: inequality, poverty, homelessness, obesity, crime, violence. It is likely that they will see ongoing increases in annual mortality on account of these factors; factors exacerbated by both the Pandemic and its associated mandates.

While Latin American populations are much younger than Eastern European populations – due to both higher births and less emigration – there will also have been a significant growth of numbers of people of peak-dying-age (over 75) contributing to ‘trend’ counterfactuals in some cases as high as New Zealand’s.

Another factor in these American countries is the high proportions of people living in or near the tropics at high altitudes. Under normal circumstances, these are unusually healthy environments, in which seasonal respiratory illnesses do not circulate as much as in temperate climes. But, it makes people living in these zones more vulnerable to pandemic respiratory illnesses when they do happen. It’s an old story that goes back to the time of Spanish colonisation in the sixteenth century.

This last factor is only apparent here in Colombia and Ecuador. Other similarly affected countries – Peru and Bolivia – had very high early death tolls, but (presumably due to political crises) have not released ‘extra-time’ data. Venezuela was even less forthcoming with useful data.

Africa including Qatar

Mortality statistics from Africa are rare. Egypt is now the best, and it certainly suffered. South Africa, which in ‘ordinary-time’ had a similar experience to that of East Europe, used to supply good quality data; but no more as its present economic crisis deepens. Signs are that the African continent was less impacted directly by Covid19 than other regions, though its more fragile economic supply-chains have become victims of the Pandemic’s ‘extra-time’ environment.

Qatar is an interesting case, because of its unusual demographics. Qatar’s resident population is heavily weighted towards the younger working-age population. So, while its death rates per capita have been very low, its percentage increases in deaths have not been low. We do need a good comparative analysis of the health impact of Covid19 on working-age populations, though made difficult by demographic data today still focusing on sex and ethnicity rather than age or occupation or labour force status.

South Asia

After China, the biggest Pandemic uncertainties relate to South Asia, with Inda being the largest country. We may also add the very populous country that is Indonesia. This region is a demographic black hole, which experiences high levels of emigration as well as of death. (We may note here – see Hundreds of Pakistanis dead in Mediterranean migrant boat disaster, CNN 19 June 2023 – that the majority of victims of the overcrowded refugee boat which sank last week off the coast of Greece were from Pakistan.) This region has suffered a huge upheaval since 2020, with the Pandemic a significant contributing factor.

Conclusion

There remains a lack of competent demographic analysis of recent and former pandemics, partly due to poor (sometimes politically-motivated) record-keeping, and partly due to the low status of demography among the social sciences. Analyses like mine here – amateur in the sense of being unpaid, but not in the sense of quality – help to fill the gap.

The most striking conclusion is that the ‘extra-time’ of the Pandemic gives a very different picture of the Pandemic’s human cost. The imposition by governments of sterile environments for long periods is not a recipe for good health outcomes, although it may give good headlines in the early phases of a pandemic when the Press is at its most attentive.

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Keith Rankin (keith at rankin dot nz), trained as an economic historian, is a retired lecturer in Economics and Statistics. He lives in Auckland, New Zealand.

Analysis by Keith Rankin.

A pandemic can end in three ways. Either the death rates attributed to the pandemic disease cease, or at least drop back to pre-pandemic levels. Or normality is re-established, with the pandemic disease still present, but displacing other causes of death. Or a ‘new normal’ is established, with higher ongoing rates of death normalised.

So, to some extent, a pandemic’s duration is a state-of-mind; meaning that the post-pandemic period is when that ’emergency’ mindset has departed. To a large extent, that happens when the most burdensome public health restrictions become untenable; in New Zealand’s case, that was when the substantive closure of the international border finished. Deaths, covid or otherwise, may still be a problem, but they cease to be newsworthy!

For most of the world, the post-pandemic period started around February 2022. East Asia was the principal exception. Table 1 below shows mortality in the first year of the new normal.

Table 1: Back to Normal?
total deaths:	2018/19*	2022/23**	increase
Macau	2199	3596	63.53%
Hong Kong	47056	62056	31.88%
Singapore	21323	26829	25.82%
Taiwan	170483	212665	24.74%
Thailand	484272	603662	24.65%
Iceland	2180	2702	23.94%
South Korea	291529	357298	22.56%
Chile	107408	130970	21.94%
Colombia	236488	285944	20.91%
Ireland	30051	35650	18.63%
Brazil	1325677	1569617	18.40%
Japan	1360950	1607011	18.08%
Northern Ireland	14998	17504	16.71%
Australia	161466	188155	16.53%
Scotland	55633	64807	16.49%
Malaysia	171015	199069	16.40%
Finland	53458	62112	16.19%
New Zealand	33310	38682	16.13%
Netherlands	148356	171826	15.82%
Germany	925309	1069924	15.63%
England & Wales	515610	592677	14.95%
Norway	39819	45650	14.64%
Austria	80544	92325	14.63%
Canada	279510	319140	14.18%
Uruguay	34655	39512	14.02%
United States	2812658	3193088	13.53%
Greece	122940	139406	13.39%
Mexico	726738	819268	12.73%
Portugal	111815	124757	11.57%
Spain	415025	458846	10.56%
Switzerland	66396	73311	10.41%
Italy	641280	705564	10.02%
Israel	45488	49996	9.91%
Denmark	53578	58826	9.80%
Peru	157650	172825	9.63%
France	591364	647762	9.54%
Czechia	110671	120448	8.83%
Slovenia	20603	22307	8.27%
Belgium	107810	116284	7.86%
Slovakia	54017	58196	7.74%
Poland	405241	435401	7.44%
Sweden	88633	94436	6.55%
South Africa	527630	561992	6.51%
Egypt	570015	605500	6.23%
Croatia	52144	55093	5.66%
Albania	21717	22900	5.45%
Hungary	131229	135090	2.94%
Kazakhstan	131089	134709	2.76%
Bulgaria	109175	112080	2.66%
Serbia	101699	104390	2.65%
Romania	263338	270222	2.61%
Moldova	37314	36554	-2.04%
*	year ended April 2019
**	latest available 12-month period

Table 1 shows a number of countries’ most recent annual death tallies compared with the year ended April 2019, the best baseline period available. May 2018 to April 2019 was chosen because it represents the first full year after the silent influenza pandemic of November 2016 to April 2018. While not a media event, that largely invisible 2017 pandemic was a substantial mortality event, at least in the ‘global north’. A pandemic does not require an authentication from WHO to be an actual pandemic. A pandemic is simply a globally widespread experience of a disruptive contagious disease.

Broadly, Table 1 shows the countries which followed ‘elimination strategies’ near the top for post-pandemic mortality. Not only did countries in the east of the eastern hemisphere (including Aotearoa New Zealand) pursue the most stringent anti-covid policies (and practiced them for the longest time periods), some  prematurely claimed to have eliminated (though not eradicated) the disease. For some in East Asia, the 2003 experience of SARS was uppermost in health officials’ minds.

Table 1 also shows that some of the countries worst-hit by the pandemic (especially those in the Southeast European ‘Balkans’) have returned to death tallies comparable with base-year numbers. If South Africa and Egypt are a suitable guide, that return to health normality applies to Africa as well.

The only West European countries with post-pandemic deaths under nine percent more than pre-pandemic deaths are Sweden and Belgium, both countries with high covid death tallies in the first wave of the pandemic, but well below European mortality averages in the second year of the pandemic. Sweden’s 6.55% increase actually overstates its situation by about two percentage points, because, more than in most other countries, deaths there were particularly and unusually low from May 2018 until the start of the pandemic. Also, Australia’s 16.53% is an overstatement, probably by at least two percentage points; this is because tardy Australia’s most recent annual deaths’ data includes the months of December 2021 and January 2022, both high mortality months compared to the following December and January.

New Zealand’s most recent death data uses December 2022 and January 2023, not December 2021 and January 2022. In contrast to Australia, New Zealand’s Table 1 increased mortality experience is understated by a percentage point, because March and April 2019 (included in the pre-pandemic baseline year) had somewhat higher deaths than those same months in 2018. If we had used a baseline year from March 2018 to February 2019, then New Zealand would have had a mortality increase of 17.40%, not 16.13%.

Re East Asia, the numbers for Macau and Hong Kong give a hint of the recent reality in China. For that region we should note also that the South Korea increase in Table 1 (22.56%) is a substantial understatement of reality, because South Korea has not reported ‘total deaths’ after July 2022, and we know that Korea has had many covid cases since then.

We also note that post-pandemic death tallies are high for Japan, Ireland, Scotland, Iceland, and Finland. These are all countries which, for their regions, were known for their more restrictive public health policies. Finland was widely acclaimed for being the most restrictive of the Nordic countries during the pandemic years. (We also note that Finland had many more deaths than Norway both pre-pandemic and post-pandemic, despite having about the same population as Norway; it suggests that many more young Finns are working abroad than young Norwegians. Likewise, we see that New Zealand has more deaths than Ireland, despite both countries having essentially the same population.)

Germany, which has had a particularly worrying recent run of deaths, in Table 1 is not out of step with its western neighbours; although we should note that southern Western Europe has generally had a post-pandemic more normal than northern Western Europe (Sweden excepted).

The critical question, looking to 2023 and 2024, is whether, for the countries towards the top of Table 1, the pandemic has triggered a new normal with persistently higher mortality than in the 2010s’ decade. Or have these countries simply experienced a delayed pandemic mortality experience which will soon subside? If the latter, then we should expect a substantial mortality drop in East Asia and West Europe in the year to April 2024.

Demography and the challenges of predicting the pandemic’s influence on 2020s’ mortality

Demography is a complex subject. Pandemic death rates per capita were high in Eastern Europe because those countries have lost many of their young people to emigration. Increases in death tallies, however, were never so high in those countries. The demography of Europe is particularly complex because many of their older people were born either side of, or during, World War Two; a war with substantial demographic consequences which have not yet fully played out.

The Scandinavian countries in particular had diverse experiences in that war. Sweden was neutral, Norway and Denmark were occupied, while Finland was successively friend and foe to the allied powers. So the change in the number of older people may differ in Sweden compared to the others. Nevertheless, Sweden still compares well with the other neutral countries: Switzerland, Ireland, Spain and Portugal. (Though noting that Spain had its own especially large demographic trauma in 1936 to 1939.)

Another problem in unravelling the demographics of Europe is the substantial international migration between present and former European Union countries, and immigration from former (or present) empire countries. So many people these days die in different countries from which they were born. We know little about the different pandemic and post-pandemic death experiences of immigrants compared to people born in the country of their death.

In most countries deaths in 2022/23 would have been higher compared to 2018/19. The main determinant of death rates is the numbers of people in the oldest age cohorts. About half of all deaths in most countries are of people in their eighties. So the biggest increases, for reasons other than the pandemic, would be due to the rate of increase or decrease of a country’s population of octogenarians. Some countries will have significantly fewer octogenarians after the pandemic, because the pandemic itself took so many.

The second most important reason for changing death tallies is the underlying health of the people. Pandemics take more people in countries which already have substantial populations – especially populations in the 65 to 74 age group – with compromised pre-pandemic health or compromised general immunity. In pandemic years, the main reason for more death is worse underlying health. In other years changes in health status may either accentuate or offset changes in the numbers of people over eighty. While there are health-compromised people of all ages, compromised health – high morbidity or low general immunity – is more likely to have prematurely fatal consequences for people aged 65 to 74.

To summarise the two previous paragraphs, I would argue that the two main predictors of a country’s normal death tally are the numbers of octogenarians in the population, and the numbers of people in the population aged 65 to 74 with compromised health or general immunity. (In addition, some developing countries still have unacceptably high levels of infant mortality.)

The two key aspects of the health status of living populations are morbidity and immunity. The countries which fare best in a novel virus pandemic (or from wave pandemics of pathogens which induce only-short-lived specific immunity) are those with low morbidity and high general immunity. With respect to the present post-pandemic period, the covid coronavirus increased both the morbidity and the immunity of populations. Where these two increases balance out, then a new normal appears which looks substantially like the old normal.

Before the twentieth century, people living rurally were more likely to experience longevity. That changed in the twentieth century, when people living in metropolises gained super-high-immunity levels from living in close proximity to each other (improving immunity); and urbanised populations experienced reduced morbidity as a result of access to a wider range of foods, from more timely access to healthcare services, less exposure to conditions such as malaria, and safer supplies of drinking water.

Big cities still reduce life outcomes for people immigrating from rural areas; for people not yet adapted to city levels of exposure to pathogens, and often having to settle for inferior housing and employment experiences. When governments tamper with the finely-tuned immunity equilibria in our big cities, the potential for deadly unintended consequences has always been there. Such tampering may include the required overuse of facemasks, and the creation of fear around the use of public transport.

The post-pandemic experience of East Asia is not a particularly good advertisement for disruptive public health practices. Sweden was conspicuous by taking the opposite policy tack from that taken in East Asia, minimising disruptions from normal social interaction. Sweden’s different approach was not a result of its greater wisdom or greater laisse-faire liberality; rather it was a result of a mistaken assumption that, by mid-March 2020, many more people had already been infected by the new coronavirus (making it too late for restrictive policies) than actually had been infected.

The interregnum between the two recent respiratory pandemics

Finally, it is worthwhile to suggest reasons why deaths in much of the developed world were especially low from May 2018 to February 2020; a phenomenon particularly marked in Sweden. This was most likely because of the 2017 influenza pandemic – the invisible pandemic (invisible even to demographers, then more attentive to issues other than heightened seasonal mortality). This world disease event left populations more immune, and (because that pandemic took so many) it meant that the post-influenza 2018 population was more healthy and had more immunity than the pre-pandemic 2016 population.

It is normal for post-pandemic death rates to be low for a couple of years. Indeed, it was true around 1919 and 1920, after the great influenza pandemic of 1918. Will it prove to be so this time, from 2023 to say 2025? We should be watching aggregate mortality – in our own countries and other countries – with as great interest as we watch the inflation, unemployment and economic growth data.

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Keith Rankin (keith at rankin dot nz), trained as an economic historian, is a retired lecturer in Economics and Statistics. He lives in Auckland, New Zealand.

Analysis by Keith Rankin.

The ‘Young Elderly’ are in essence the post-war baby-boomers. An average young elderly person in these charts was born around 1950 to 1952.

The charts look at ‘quarterly excess deaths’, so do not show week-by-week fluctuations in deaths. For example, data for the very end of 2022 covers the whole of the last three months of 2022.

As in my previous recent charts (see my Spiralling Deaths in Germany, Evening Report, 14 March 2023; and Examples of Germany and Denmark, Evening Report, 12 March 2023), I have emphasised Germany, because late-pandemic mortality has been so bad there. And because Germany’s differences with the rest of Europe create a very useful point for epidemiological analysis.

In the first chart (above), of the countries shown only Germany and New Zealand had excess deaths in this age group below ten percent in the first six months of Covid19. The United Kingdom was easily worst then.

The United States had a really bad pandemic, for two years from April 2020 to April 2022. But, subsequently, for nearly two years since April 2021 Germany has been for the most part easily the most deathly of these countries, for the young elderly, with only the USA contesting Germany for this dubious honour. For some of 2022, New Zealand was in second place out of these seven countries.

We note that Belgium, Netherlands and France all had high death rates early in the pandemic, but have subsequently had much lower death rates than Germany for this age group.

The two obvious avenues for investigation are diet (the French surely have a more healthy diet?) and differences in the policy responses to the Covid19 pandemic. My understanding is that, while all countries had similar public health restrictions during the peak weeks of Covid19, Germany was much the slowest of these countries to remove mandated public health measures. Germany’s abundance of caution may have backfired big-time. Yet the only reason given here (on Deutcshe Welle) is: “that diseases other than Covid19 are bouncing back because fewer people are wearing masks amid a general relaxation of pandemic rules in comparison with the past two years”. There is no hint of comparative analysis in this particular DW media report.

The second chart compares Germany with its four nearest Eastern European countries, and with the two Mediterranean countries which were the first to experience substantially elevated pandemic death rates.

For the young elderly ‘boomers’, Spain and Italy show quite the opposite pattern to Germany; they started with high death rates and then moved to generally lower rates. Both had summer mortality peaks in 2022, to some extent due to the summer heat waves but mainly due to the rebounding of tourism with Covid19 still present. Covid19 flourishes in bars and restaurants, and in airport terminals.

The eastern countries had more deaths overall in the middle seasons of the pandemic, despite (or maybe because of) the success of the measures taken in the early months of the pandemic. Also, for these countries, with lower life expectancies than their western neighbours, the young elderly are on average closer to their eventual deathdays. It is important to note that these eastern countries had the fewest pandemic-related deaths after March 2022. Presumably their people most at risk of dying had already died, and the remainder had higher natural immunity to respiratory illnesses than did the older citizenry of Germany. (I am not aware that Polish, Bohemian or Hungarian cuisine is particularly noted for its health benefits, in contrast to the much-touted Mediterranean diets; so a better diet is probably not the reason.)

There is one other country with a similar pandemic death-profile to Germany; its southern geographic and cultural neighbour, Austria. The final chart here shows the smaller countries of western and central Europe, plus New Zealand. (Australia and Sweden do not provide age-group data.)

First we note that Austria and its neighbours Slovenia and Switzerland start out closely synchronised. Switzerland drops off Austria’s high young-elderly mortality path from March 2021, and Slovenia drops off a year later (though has a high summer peak in line with its Italian neighbour). The Scandinavian countries had generally low death rates for the young-elderly age group. (They did however see rising deaths from mid-2021 for the older elderly.)

Any valid epidemiological analysis for Germany’s 2022 tragedy needs to take into account the similar experience of Austria, as well as the generally different experiences of the other European and neo-European countries.

The United States still has a worse overall pandemic record than Germany, for the young elderly. The worry for Germany, though, is that the reasons for its really bad 2022 have not necessarily been resolved; 2023 may be just as bad. Time will tell; so long as an asteroid strike or a nuclear war don’t displace infectious diseases as drivers of excess mortality in Europe.

Keith Rankin (keith at rankin dot nz), trained as an economic historian, is a retired lecturer in Economics and Statistics. He lives in Auckland, New Zealand.

https://www.dw.com/en/winter-illnesses-burden-germanys-intensive-care-units/a-64135331

https://www.dw.com/en/top-german-virologist-says-covid-19-pandemic-is-over/a-64214994

Germany’s Deadliest Weeks since World War Two? – Spiralling Deaths in Germany

The four weeks ending 8 January 2023 have seen easily the most deaths in Germany of any four‑week period since 2015. The worst week was the week ending Christmas Day, with 28,481 deaths. While it’s hard to compare with pre-1990 years, due to the East Germany question, it may well be that this week last December had a greater percentage of excess deaths than any other week since the last world war.

Baseline weekly deaths for 2022 would have been just over 17,000; a baseline of 68,700 for four weeks, as shown in Table 1.  Therefore, winter illnesses have raised peak deaths at the end of 2022 to 65 percent above what they would have been in a normal non-winter week.

While the December 2022 statistic is remarkable, it seems that most Germans themselves are not aware of this. Many people suffering individual tragedies will typically not be aware if their ‘micro’ tragedy is part of a much bigger ‘macro’ tragedy. This DW story (23 Jan 2023) The impossible task of calculating global pandemic deaths, only looks at 2020 and 2021, and gives no commentary on the Germany chart included. The best I can find on DW discussing the health situation in Germany last December is: Winter illnesses burden Germany’s intensive care units, 17 Dec 2022.

What is remarkable is that this latest winter toll comes very soon after three other periods of high peak mortality in 2022, listed in Table 1 as ‘autumn wave’, ‘summer wave’, and ‘omicron wave’. So, from the Grim Reaper’s point of view, the ‘low-hanging-fruit’ should already have passed.

These recent mortality waves compare unfavourably with the three ‘classic’ Covid19 death waves, each of which had weekly peaks in 2020. By ‘classic’ I mean the original ‘Wuhan’ coronavirus strain, before ‘variants’ and ‘vaccinations’ became a thing in 2021.

It is also noteworthy how high some of the pre-covid death peaks were. The influenza ‘pandemic’ of late 2016 to early 2018 was particularly pronounced. (I use single-quote-marks, because this actual pandemic was never granted pandemic-status by the World Health Organisation.) Germany’s two peaks for this influenza pandemic were in February 2017 and March 2018. We also note a particularly bad season of epidemic influenza in early 2015.

Refer to my Death Spikes and Covid Dissonance? Examples of Germany and Denmark for charts recently published, comparing Germany’s excess deaths with those of its neighbour, Denmark. The December 2022 mortality peak is reproduced to some extent in most (but not some eastern) European Union countries, and in the United Kingdom and United States. However, Germany’s year-of-death in 2022 is probably the most dramatic. (One other country which appears to have an equally problematic mortality, maybe worse, in 2022 is South Korea. I wait in hope for the eventual publication of South Korea’s complete dataset.)

Chart 1 below shows ‘excess deaths’ – as distinct from total deaths – for Germany, by age group.

Chart 1

Germany’s demographics are unusual (but maybe not unusually unusual) on account of World War Two. The oldest Germans – shown in red – were all born before that war. The German post-war baby-boomers are shown in green. Germany shows disturbingly high rates of pandemic death for its baby-boomers, from 2021. (It should be noted that Covid19 deaths tended to peak from November to January, whereas epidemic influenza death tended to peak in February or March. Thus the big reductions in excess deaths each February and March are mainly due to high death-norms set by pre-covid influenzas.

Countries regarded as having pursued the best anti-Covid19 public health policies in 2020 have not had a good 2022. Germany is one of those countries. South Korea, Japan, Taiwan, Thailand, Singapore and China are others. So are Australia and New Zealand. Once having acknowledged the 2022 death statistics for what they are, terrible, the question is whether the problems of 2022 in these countries will extend into 2023. While my hunch is that new vaccinations could make a difference, in 2023 at least, I am concerned that societies have already passed a demographic turning point and that life expectancies are already declining from their peaks, and may continue to decline for decades.

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Keith Rankin (keith at rankin dot nz), trained as an economic historian, is a retired lecturer in Economics and Statistics. He lives in Auckland, New Zealand.

The chart above is quite alarming, and not only because of Germany’s high death toll. It’s the difference between reported Covid19 deaths and excess deaths, in the context where four waves of excess deaths in Germany in 2022 are clearly ‘epidemic’ in nature. And we see the same death waves in Germany’s northern neighbour, Denmark.

Both countries are assiduous in releasing their demographic data on deaths; most countries are not. And both countries had a reputation for having among the best sets of public health data re the Covid19 pandemic. Yet while public health data may be released with much media fanfare, demographic data usually is not. While certain public health data might be classed as ‘black verse’ poetry, and hence of interest to mainstream media, the more prosaic data sourced from ‘births, deaths and marriages’ tends to be overlooked.

In both countries, easily the worst month for epidemic deaths this decade has been December 2022. Yes, 2022, not 2020. In both countries, the people would seem to be largely unaware of this collective death experience. (Awareness would largely be confined to people’s own families.)

The widely endorsed supposition is that the pandemic is over; a concept that may mean different things to different people. To an epidemiologist, an ended pandemic may be followed by a new era with a new normal of permanently higher death rates. To the lay public, or to the pollyanna-ish finance industry which never stops telling us that we are all going to live longer, an ended pandemic means a return to something like pre-covid normality.

I watch DW (Deutsche Welle) world news semi-regularly, and I have heard nothing about the December death spike in Germany. The few stories on DW that I have found in a search today are these:

Winter illnesses burden Germany’s intensive care units, 17 Dec 2022.

Top German virologist says COVID-19 pandemic is over, 26 Dec 2022.

Germany’s new COVID debate [about removing Covid19 restrictions], 29 Dec 2022.

Are Germany’s hospitals in critical condition?, 5 Jan 2023.

WHO discusses end of COVID-19 emergency status [mainly a reference to China], 27 Jan 2023

So, as in New Zealand, there’s acknowledgement of overstretched hospitals and seasonal illnesses. There’s little suggestion that the main culprit is another covid wave, and we certainly have no indication that Covid19 has recently become more virulent.

We should also note that excess deaths in Europe have looked quite dramatic, since 2020, each December. This is because ‘normal’ influenza outbreak deaths – in the 2010s at least – tended to peak in February, not December. The big falloff in excess deaths from January 2023 is to some extent due to death numbers needing to be higher to be classed as ‘excess’.

Both countries started to downplay their reporting of Covid19 deaths from mid-2021; with the exception of Denmark during the first ‘Omicron wave’ of early 2022. We can see that, in February and March 2022, many people in Denmark died of or with Covid19, while significantly fewer people died of other causes. (This substitution of death-causes was much less true for Germany.)

But the situation in Denmark reversed in December 2022, with many more excess deaths than reported Covid19 deaths. Indeed, in Denmark there were five death waves in 2022, and all (except perhaps the relatively small June death wave) correlating with reported Covid deaths (but see the Denmark chart below); expect that the peaks in reported deaths have been increasingly lagging the actual death peaks. The Denmark data in this chart definitely points to all of these death peaks as being associated with recurring waves of Covid19.

We certainly see the same lags in the German data, although the reported death waves are less pronounced. Generally the ‘peaky’ nature of the data suggests that these populations have been facing repeated outbreaks of respiratory viruses; outbreaks for which their immunity levels have been decreasingly able to cope. While waning immunity appears to be the main problem – a problem long known in relation to human coronaviruses – and that waning immunity here likely relates in particular to vaccination immunity, it is also possible that each wave of infection creates new morbidities in the most vulnerable people. So, a combination of waning immunity – covid immunity and general immunity – combined with new comorbidities is leading to progressively higher death tolls. We also note that December in particular is a month characterised by much social ‘mixing and mingling’; conditions ripe for coronaviruses transitioning from epidemic to endemic.

These two charts, for each country separately, also include ‘case’ information. Again, while underreporting is also an increasing feature of case data, this is data that underpins the timing of Covid19 outbreaks (as distinct from non-covid respiratory viruses). Nevertheless, case data may also lag actual deaths, as people are slow to test for covid, and report, until they are fully aware that a new outbreak is taking place.

When we look at Germany, we can clearly see the correlation of case data (in blue) with excess deaths (in red). When there were new covid variants, as in March 2021, August 2021, and January 2022, we can see the uptick in reported cases leading the uptick in deaths. Otherwise, we tend to see the uptick in deaths coming first, with case reporting lagging ever-further behind. December 2022 was particularly striking, with an eventual upsurge in cases suggesting that a significant number of people who died in the death spike were indeed infected with the coronavirus. In Denmark the pattern of excess deaths correlating with reported cases of Covid19 is, if anything, even stronger.

If we think of Covid19 as a three-year pandemic, we can see that in both countries the second half of the pandemic was worse than the first half, regardless of the official cause of death attributed to each casualty.

A death is a death is a death. To dying persons, and their families, it matters little if a death is directly or indirectly caused by Covid19. An indirect death may be due to a loss of general immunity, or to any other factor linked either to the biology of the virus, to fear-induced behaviour changes arising from the attention given to the virus when it was a big story, or to the government mandates ‘to keep us safe’ but which may have (to some extent) substituted one risk for another.

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Keith Rankin (keith at rankin dot nz), trained as an economic historian, is a retired lecturer in Economics and Statistics. He lives in Auckland, New Zealand.

On 7 March 2023 I published a summary table of death tallies in a wide range of countries, comparing 2019‑2022 with 2015‑2018. (Covid19 Pandemic-era Facts: Irrefutable, Inconvenient, Important, Evening Report.)

I let the data stand on its own, largely without interpretation. The most important findings to explain are the reasons why Sweden weathered the Covid19 pandemic so well, and why East Asian countries fared so poorly. These facts run counter to the mainstream narrative; a narrative which has presumed that the truth is the precise opposite of what the recently available data shows. East Asian countries relied very heavily on government mandates and the compulsory wearing of facemasks for extended time periods. Sweden, on the other hand, came to be known for adopting one of the least interventionist public health policies during this early-2020s’ pandemic.

This is the main issue that needs to be explained. The demographic data, of course throws up other issues as well – including the high death tolls in the USA and the remainder of the Americas, and the lower toll in Eastern Europe than might have been expected given earlier health data. Demographic imbalances may be contributing to countries’ different experiences; imbalances relating to diverse and changing birth rates and economic migration, in addition to life expectancy issues.

Interpretation

To answer a question such as the main query posed here, we need data, at least one hypothesis, and at least one counterfactual. We also need a contestable academic environment, whereby multiple interpretations can be freely posited and reasonably argued.

We have an important set of data in my report in Evening Report.

The hypothesis that I posit is that pandemic-related mortality in general has been lowest in societies which have good balances with respect to pathogenic exposure and hygiene, that imbalances lead to reduced levels of general immunity and/or raised levels of morbidity, and that societies with high levels of general morbidity will have more excess deaths during an event such as a pandemic; indeed, during any catastrophic event.

It is possible to have too little (as well as too much) exposure to environmental pathogens. In these situations, there are two types of risk – which statisticians, prosaically, call Type 1 and Type 2 – and the reduction of one type of risk in itself raises the other type of risk. The recently oft-said phrase ‘an abundance of caution’ is an example of attempts to reduce Type 1 risk.

In teaching statistics, it is commonplace to use a criminal courtroom setting to explain these risks. A ‘risk-averse’ approach (ie an ‘abundance of caution approach’) is to acquit an accused person if there is any doubt whatsoever about the person’s guilt of the crime in question. The expression ‘beyond reasonable doubt’ expresses balance; the expression ‘beyond all doubt’ expresses an abundance of caution.

It is easy to see that, minimising the risk of an innocent person being convicted also increases the risk of a guilty person not being convicted (and thereby being ‘free’ to commit further crimes); this is the ‘Type 2’ risk. Reduced risk to the defendant means an enhanced risk to society.  ‘An abundance of caution’ simultaneously means ‘a scarcity of caution’; more caution with respect to pathogen exposure means less caution re general immunity deficiency. (The quality of the evidence – eg the data – minimises both types of risk; it also minimises the quality of interpretative reasoning in relation to that evidence.) In pandemics, a good practical compromise is to adopt ‘Type 1’ caution for a brief period of acute danger associated with an unknown threat, and to as soon as possible to revert to a normal ‘balanced caution’ approach.

The most straightforward counterfactuals are purely demographic. And comparative. This is why we need much better, and more comprehensive, demographic information. Demography is the statistical analysis of births, deaths, and migrations. The most important demographic variable is a person’s ‘age’. While race/ethnicity/ancestry, sex/gender, and (to a lesser extent) religion are also demographic attributes, ‘age’ is more important to understanding outcomes (noting that the most important demographic ‘outcome’ is death). Age is the most important predictor of a person’s likelihood of dying; after that, it is socio-economic and lifestyle attributes such as income, housing, education, happiness (leading a meaningful life) and access to healthcare services which determine the likelihood of both mature and premature death.

In the context of Covid19 pandemic mortality, the counterfactual is what levels of mortality would have occurred had there been no Covid19 and hence no pandemic. The usual ways to establish such a pandemic counterfactual is to evaluate and project normal patterns of mortality in the previous few years; if necessary making comparative-country adjustments for any abnormal events in those prior years. And then to use those normal data to predict an ‘alternative present’; in essence, this process of forecasting the immediate past is a valuable use of forecasting techniques.

The next process is, if possible, to compare your (affected) place (eg country) with some other place (or places) which were unaffected (or lesser affected) by the phenomenon you are seeking to evaluate. Some countries are better comparators than others. While Australia – with its many cultural and economic similarities –  is the most widely used comparator for New Zealand, Scandinavian countries are also widely used.

With a pandemic, no country is unaffected. But countries pursuing different public health policies become useful comparators; they help to answer the question as to what would have happened had one country followed another country’s policy. Thus, Sweden’s experience can be built into a counterfactual for New Zealand, because Sweden’s policies were different in both substance and in style. Australia is less useful because its pandemic public policies were very similar to New Zealand’s.

So, a simple counterfactual for New Zealand would be to project 2015‑2018 mortality data into the 2019‑2022 period. The documented excess of deaths compared to that counterfactual represents an estimate of New Zealand’s ‘quantity of life’ pandemic outcome. Then, repeating the exercise for Sweden yields a comparable quantity of life outcome for that country. The country with the smaller percentage excess of deaths probably pursued the better set of policies, noting that two quite different policy approaches could yield similar outcomes.

A well-reasoned counterfactual is an essential part of any interpretation of historical facts. In a scientific process, for which the reasoned use of counterfactuals is an example, a counterfactual is commonly called a ‘control’. It was widely noted (eg in the book The Herd) in 2020 and 2021 that Sweden potentially contributed substantially to the scientific understanding of the Covid19 pandemic, by providing demographers and epidemiologists with a control. So far, however, I have seen little evidence that Sweden’s value as a control – as an important policy counterfactual – has been well-utilised.

The quality of demographic information throughout the world is rather poor. While New Zealand is better than most countries, getting good information about the ages of the population (and where people of different ages live) is difficult. Indeed, until a few years ago, demographic information about immigrants and emigrants was collected somewhat casually as an accessory to tourist data. (Indeed, re yesterday’s ‘compulsory’ population census, the government’s target was only ninety percent compliance; meaning it is regarded as acceptable to ignore the 500,000 ‘harder to reach’ people in this country.) Travellers were assessed as immigrants – rather than visitors – based on their stated intentions on arrival, and not on the actual outcomes of their travel. Many of the people who die in New Zealand are not born in New Zealand, and vice versa.

This makes it hard to create good projections of what mortality in any country, let alone the world, would have been from 2020 in the absence of the Covid19 pandemic. Nevertheless, indications are that, in the absence of the pandemic, New Zealand would have had a higher increase in mortality (maybe a four percent increase from 2015‑2018 to 2019‑2022) than most other countries in the world would have had. This finding relates in particular to New Zealand’s particular pattern of aging, noting some substantial variations in birth rates in the years from 1930 to 1960; and, also variations in the age distribution of older foreign-born New Zealanders.

There are other indications, based on the use of the United States as a comparator country, that some of the increases in morbidity occurring in the USA before 2020 were also occurring in New Zealand; for example, reasons around income inequality, housing, and mental health. The pandemic in USA was substantially more severe than in Sweden, with New Zealand falling in between.

Evaluation of the Hypothesis

In New Zealand, an excessive emphasis on hygiene – including the mandated wearing of facemasks in many public settings – most likely contributed to a loss of general immunity to infectious diseases. New Zealand, by in large, followed the East Asian public health policy model.

This loss of general immunity was countered by a comprehensive, though belated, Covid19 vaccination programme. Vaccination immunity almost certainly contributed to low excess mortality in the period from October 2021 to March 2022. But specific immunity (whether arising from infection or vaccination) to coronavirus diseases – which include around ten percent of ‘common colds’ – and influenzas has always been known to be short-lasting. So general immunity that arises from lifestyle factors remains an important protector of life; general immunity is enhanced by balanced diets (avoiding excesses of foods that create morbidity, such as alcohol, sugar, some fats, and salt) and some ongoing exposure to a range of less-dangerous pathogens.

People living in West European urban environments probably have had closer than most other people to ideal levels of balanced nutrition and general immunity. So these countries have generally had the least pandemic mortality, and (if my hypothesis is correct) probably have the best outlook for the next few years with respect to deaths arising from respiratory infections. People living in Eastern Europe, especially in the European Union, seem to have regained high levels of general immunity, though they bore a high cost in 2021; and membership of the European Union gives them lifestyle options not available in many other countries.

My hypothesis, if correct, suggests that excess deaths will continue in East Asia for another year or so, due to compromised general immunity arising from excessive hygiene. And, in the Americas, increased morbidity seems to be a growing socio-economic problem, making those populations particularly vulnerable to respiratory pandemics. Both of these regions will experience increased levels of morbidity arising from the after-effects of Covid19 infections.

Africa and South Asia are hard to evaluate due to lack of data. But, for Africa at least, indications are that Covid19 excess deaths have been less than in the Americas, and maybe even comparable to Western Europe. Lifestyle morbidity remains less in Africa as a whole than in the Americas. And general immunity levels in Africa have always been high; it is a continent widely associated with ongoing pathogenic exposures. The critical factor for Africa in the coming years will be nutrition. South Asia most likely the same, though with complications arising from substantial air and water pollution.

New Zealand and Australia? Harder to predict, based on my hypothesis, because both countries contain elements of the East Asian, American and Western European experiences. I just hope that New Zealanders are able to get their pre-winter boosters in time. There is every reason to anticipate a dangerous new outbreak of Covid19 in the early winter, much as occurred in Western Europe in the three months to mid-January 2023.

To get to the truth we need reasoned argument, scientific argument. The pandemic has touched on our lives sufficiently to deserve mainstream media attention be given to contestable analysis of its impact; and to question politicised narratives of the form ‘the science says this’ when in fact science is a contestable and argumentative process.

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Keith Rankin (keith at rankin dot nz), trained as an economic historian, is a retired lecturer in Economics and Statistics. He lives in Auckland, New Zealand.

The most important question about the Covid19 pandemic of the early 2020s is ‘how many people died?’. (The second-most important question relates to the impact of the pandemic on people’s ‘quality of life’.) The data here, available since last week, is the starting point for an answer to the first question. This data is as close as can be got to ‘pure facts’, ‘body counts’ in which no expert interpretation plays a role. (This contrasts with ’cause-of-death’ data which requires a doctor’s opinion.) This is raw data. Raw data is true.

There is not really such thing as a ‘global pandemic’, because a pandemic is, by definition, a global event. In a pandemic, individual countries may be understood as ‘administrative regions’. National differences of mortality during a pandemic will be a mix of fortune, prior circumstances, and quality of administration. Re ‘quality of administration’, ‘body counts’ – while most important – do not represent the whole story. We note here my second-most important question, above.

The data above will never be a global total, no matter how long we wait for laggard countries to report. Some countries simply don’t register deaths; these countries are mainly in South Asia and Africa. Some other countries do not share their death tallies with the rest of the world.

The data above is irrefutable, in that it is a simple count of deaths, covering two periods each of four years (209 weeks for those countries which report on a weekly basis). This contrasts with ‘official’ Covid19 death tallies which depend, in each administrative jurisdiction, on some interpretation of what counts as a Covid19 death. ‘Total deaths’ data does not distinguish direct from indirect pandemic deaths.

For most countries, regardless of covid, there would have been an increase in deaths in the most recent ‘quadrennium’ (four-year period) vis-à-vis its predecessor. The major single cause of such covid-unrelated increased deaths is changes in the numbers of ‘elderly’ people, with the precise age of ‘elderly’ being higher in some countries (say Denmark) compared to others (say Lithuania). A country with a high proportion of elderly people need not have a higher percentage increase in deaths from one period to another; however, in these times, most countries are experiencing faster annual increases in their elderly populations than in their younger people.

One complication here is that World War Two ended in 1945, meaning that in 2020, a person born in 1945 turned 75 in 2020. While we are very sure that most countries had higher birth rates after 1945 than before, we are less sure about which countries had the biggest post-war ‘baby booms’.

One question that may be asked is ‘why include 2019 with the other pandemic years?’, given that the pandemic started in 2020. There are two reasons. First, as we have eight years of data conveniently tabulated by ourwordindata.org, the simplest procedure is to compare one quadrennium against the other. The second reason is that death rates in one year may ‘inversely’ impact on the following year’s data. Countries which have above-average levels of epidemic influenza in the year-or-so before a pandemic are likely to have reduced deaths in the first year of that pandemic, because many of the people most vulnerable to infectious diseases have already died. Likewise, re the present pandemic, a benign influenza year in 2019 (such as in Sweden) would of itself postpone deaths until 2020.

Table 1 is not a ‘league table’ of administrative competence, jurisdiction by jurisdiction. Nevertheless, the data shows broad categories of national experiences, and interesting variations (and non-variations) between countries regarded as like. It is a factual unnuanced measure of the different experiences of the Covid19 pandemic in different countries.

Some data highlights:

Scandinavia

As with many social indicators, Scandinavian countries had the lowest amounts of ‘increased death’ arising from the covid pandemic. Within that Nordic group, Sweden is a clear ‘winner’. This is particularly interesting because Sweden gained much publicity in 2020 for its contrary approach to public health administration during the pandemic. Sweden’s state epidemiologist, Anders Tegnell, famously said that Covid19 was a “marathon, not a sprint”. The marathon is now over, and Sweden has at least taken ‘line honours’.

However we should note that Sweden’s second-worst month (for excess deaths) for the whole pandemic was December 2022. (Its worst month was April 2020.) This significant though largely unnoticed fact is also true for other Western European countries. For some the 2022-2023 festive season was the worst three weeks for the entire pandemic. So, we may be looking at Covid19 as an ‘ultra-marathon’ rather than a marathon; if so, we still have years to wait before we can conclusively evaluate the demographic consequences of this pandemic.

The countries which ‘did best’ in the pandemic were those able to confine most of their covid-diagnosed deaths to people who, had they not died of Covid19, very likely would have died from other causes during the pandemic quadrennium.

Western Europe

Countries in Western Europe outside of Scandinavia had increased deaths mainly in the six‑percent to ten‑percent range, with Belgium and Netherlands both just outside of that range (though on either side of it). Interestingly, in the first wave of Covid19, Belgium had many more recorded covid deaths (per capita) than Netherlands. But it was Netherlands which ended up with an ‘above 10 percent’ increase. Netherlands had a bad pandemic.

The United Kingdom came very much in the middle of the Western European ‘pack’.

Two other ‘western’ countries to note are Canada and Israel. Both have increased deaths higher than the European Union and United Kingdom countries.

Australasia

Australia and New Zealand have increased deaths very similar to Western European levels.  ‘Officially’, both have reported fewer covid deaths per capita than do these European countries. This may be due in part to unusually large increases in the elderly populations of Australia and New Zealand; if so, many of these recent additional deaths will be neither directly nor indirectly due to Covid19.

Eastern Europe and East Asia

Both these groups of countries have, for the most part, increased deaths in the ten‑ to twenty‑percent range. This, for East Asia at least, may be a big surprise to the many people who believed that East Asia set the exemplar for best public health policy during the pandemic.

In East Asia, South Korea is a country of particular concern. South Korea has not released weekly death tallies since July 2022; it used to be a reliable reporter of such data. Subsequent Covid19 case data from South Korea suggests that it has experienced two recent waves of Covid19.

Another country for which the Table 1 data may be understated is Hong Kong. December 2022 was known to be China’s worst month, and this showed in the alarming excess death toll for Macao (Hong Kong’s close neighbour) for that month. So the recent Hong Kong data may be substantially revised, or we may see a much bigger toll for Hong Kong in January 2023. (We should note that, in the United Kingdom, there are signs that many people who die in the end of any December have their deaths counted in the following January. Different administrative practices can may weekly data hard to compare across countries.)

For Eastern Europe, I have generally restricted this table to countries in the European Union, though I have included Serbia, showing that its experience is comparable to its European Union neighbours. Eastern Europe did particularly badly in the ‘official’ Covid19 death tallies, in large part due to their high proportions of elderly people. Eastern Europe is a major source of economic migrants. (And, with lower life expectancies than in Western Europe, the threshold age that defines ‘elderly’ in these countries is lower. We may note, as a matter of interest, that the typical life expectancy in Eastern Europe is comparable to New Zealand’s ‘Pasifika’ population.)

An interesting group of Eastern European outliers are the Baltic countries: Lithuania, Latvia, and Estonia. While these recorded high numbers of Covid19 deaths relative to their total populations, the percentage increase in deaths is not so large. This is due to their high but unchanging prevalence of older people. Indeed, their populations probably got slightly younger in 2020 and 2021, as previous high levels of youth emigration will have been stemmed by Covid19 public health controls within the European Union.

South America and the United States

The typical increase in deaths for South American countries is between twenty and forty percent, with Uruguay, Chile and Brazil looking best for those countries with available data. (Argentina is extremely slow at releasing its total death tallies.) Uruguay is easily best.

The high Covid19 mortality of the United States is very apparent in this simple tally of deaths. Indeed USA probably compares better with South America than it does with its European allies. The demography of the United States is like that of New Zealand in some respects, but like South America and Mexico in other respects. Western European (and Australasian) populations have life expectancies above 80. The USA and most South American countries do not. While Covid19 was a disaster for the United States, it may not be that the different public health responses within USA made much difference. It may be that certain known comorbidities – such as diabetes, drug dependency, mental unwellness – are more present in American than in European populations.

Further Interpretation

I have here confined my interpretation of the data to the points which would be best understood by a professional statistician. Further interpretation takes us into the realm of scientific speculation. The science – the testing of plausible explanatory hypotheses with adequate datasets – needs to be done.

The first question begged by the data presented here is why Sweden in particular (and Europe in general) have come out of the pandemic rather well (so far! the ultra-marathon is far from over). The second question is why East Asia has come out so poorly, despite early indications to the contrary.

Sweden coming out of the pandemic marathon so well, and East Asia so problematically, is the inconvenient counter-narrative which happens to be the truth – the poorly understood truth – of the matter.

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Keith Rankin (keith at rankin dot nz), trained as an economic historian, is a retired lecturer in Economics and Statistics. He lives in Auckland, New Zealand.

Quantity of Life

With mortality data now available for many countries to the end of 2022 (and, for a few countries, for a month into 2023), we are now able to properly assess the demographic cost of the Covid19 pandemic. There is a proviso, in that for a number of countries, December 2022 experienced substantial covid-related mortality, suggesting that the demographic consequences will last into 2023 and probably 2024. The demographic cost includes mortality indirectly caused by both the disease itself and unintended consequences of the public health measures taken to contain the covid coronavirus.

It is important to note that there is an additional impact – the socio-economic impact – arising from the pandemic; a disruptive impact on the living, adverse on balance, that cannot be measured by death tolls, though which may be reflected if life expectancies beyond 2023 fall below previous projections. This is a ‘quality of life’ rather than a ‘quantity of life’ consequence of the public health events of 2020 and 2020.

We also need to note that, with eight years of data shown, we can compare the death tally for the second four years’ [2019‑22] directly with the first four years [2015‑18] (both representing ‘quadrennial’ periods of 209 weeks). It is appropriate that 2019 is included with the subsequent pandemic years, because events in 2019 may contribute to 2020 death numbers; in particular, if 2019 had lower than usual seasonal illnesses, then many people who would normally have died in the winter of 2019 would have died in of 2020 or 2021 instead.) We note that, for the pre-covid years in the 2010s’ decade, the winter death peaks (typically late winter in the northern hemisphere) mainly relate to influenza, with a more general seasonal mortality effect triggered by ‘common colds’ and the like.

(And one piece of technical information. The weekly death tolls charted have been ‘smoothed’ to reduce the effects of random variation. Thus, the peak numbers for Australia and New Zealand – in July 2022 – each represent a weighted average of the deaths for that actual week and the deaths for the weeks immediately before and after. It means that the actual numbers of deaths in the peak weeks were higher than shown.)

Australia and New Zealand

I start with Australia, which in the past I have been unable to chart very well because the Australian authorities are unnecessarily slow to release mortality data, and when they do it’s typically up to ten weeks of data at a time. We note, with reference to the New Zealand chart, that Australia’s population is slightly more than five times more than New Zealand’s, and has a similar age structure.

A baseline mortality toll for Australia in the early 2020s would be 3,000 deaths per week; it is shown by the black ‘predict 2020’ plot on the chart. The pattern of increasing deaths from 2015 to 2019 is mainly due to population increase; particularly, increased numbers of people aged over 70. (Baseline pre-pandemic weekly mortality for New Zealand is about 600.)

The scale of these charts is (approximately) with the top number (eg 5,000 for Australia) being double the bottom number (eg 2,500). In the first year of the pandemic, 2020, Australia’s weekly death tallies were much like what would have been expected in a non-covid year, but with lower winter deaths. That 2020 experience reflects the public health restrictions which were imposed, with the international travel restrictions probably being most important.

The demographic cost – in deaths – really begins in Australia in April 2021, and clearly persists to the end of (and most likely beyond) 2022. (A look at my previous set of chartssuggests that, based on northern hemisphere experiences of late 2022, mid-2023 – winter – could be particularly bad in the southern hemisphere; although taking advantage of the seasonal time-lag to get suitable vaccination programs in place may help the ‘lucky south’.)

New Zealand data reveal a broadly similar pattern to Australia, though the 2020 shortfall of deaths was more accentuated, and the more general appearance of excess deaths began seven moths later than in Australia, in November 2021. New Zealand, having a much smaller population than Australia, shows more exaggerated peaks and troughs; and generally more ‘random noise’, more random variability, from week to week.

Australia’s pre-covid estimated life expectancy (source: IMF database) was 83.4, with a median population age of 37.9. For New Zealand, the comparable numbers were 82.3 and 37.9; so, both countries have very similar demographics.

I have calculated the increase in quadrennial (ie four-yearly) total deaths for 2019‑22 compared to 2015‑18. For Australia, with December 2022 data still missing, it’s an estimated 7.9% increase in deaths. For New Zealand it’s 8.2%, slightly higher. For both countries, 2022 is the year that most contributed to the 2019-22 excess deaths’ toll. In addition to Covid19, increases in these countries’ populations of elderly will have contributed to higher mortality this decade.

Finland and Sweden

Finland has just a few hundred thousand more people than New Zealand. Its 2019 estimated life expectancy was lower than Australia’s and New Zealand’s, at 81.9. And its median age, at 42.8, suggests that Finland should have a significantly higher base rate of deaths per week. Indeed, the chart shows a base weekly tally of about 950, substantially higher than New Zealand’s 600.

Finland was the most restrictive of the Nordic countries, with respect to public health management of Covid19. It’s pattern of weekly deaths looks very similar to New Zealand’s, with New Zealand having a six-month (seasonal) lag. This means that the extent that Finland’s deaths are above baseline from July 2022 seems likely to be a good predictor for New Zealand in the first half of 2023.

Finland had 7.2% more deaths in 2019‑22, compared to the previous four years. The main explanation for its lower mortality increase (than Australasia) is likely to be due to a lower rate of increase in the size of its elderly population.

Sweden has close to double New Zealand’s population, and had almost the same pre-covid life expectancy as Australia and New Zealand (82.8). Its median age was 41.0; lower than Finland’s, probably due to both more immigration (especially refugees) and (given Finland’s membership of the Eurozone) less emigration than Finland to places like Berlin and Brussels. As Sweden’s chart shows, Sweden’s pre-covid baseline mortality was about 1,600 deaths per week, equivalent to 800 in New Zealand; again, higher due to Sweden having relatively more older people than Australia or New Zealand.

Unlike the other countries mentioned so far, Sweden had almost all its pandemic excess mortality in the year commencing March 2020. One important reason for this was Sweden’s unexpectedly low mortality in the year-and-a-half prior (especially in the winters of 2018/19 and 2019/20) to Covid19, meaning that many of the covid deaths of the frail elderly in Sweden in 2020 were people who, based on statistical expectation, would normally have died before the pandemic struck. The other main reason for Sweden’s high early toll was its classically liberal public health policy approach.

2021 in Sweden looks very much like a normal pre-covid year in Sweden. In the second half of 2022, all west European countries had significantly elevated mortality, mainly it would seem associated with renewed Covid19 outbreaks. Comparing Finland and Sweden, both had December mortality peaks about 50% above baseline weekly death tallies. But Finland clearly had much worse autumns than Sweden, in both 2021 and 2022.

In an important sense, many people died in Finland in 2021 and 2022 who would have died in 2020 were it not for the public health mandates then operating in Finland but not Sweden.

There’s more to it than that though. Sweden’s increase in deaths for 2019‑22 compared to the previous four years was just 2.2% compared to Finland’s 7.2%. It looks as though Sweden’s population had a significantly higher level of general immunity in 2021 and 2022 than did Finland’s. Finland experienced a greater overall demographic cost from the pandemic – presumably in large part because of its different policy choices – than did Sweden.

Both of these Nordic countries (and the other Nordic countries too) had a lower increase in deaths than did Australia and New Zealand. But the Australasian countries probably had bigger increases in the elderly populations (defining ‘elderly’ as over 70); nevertheless, Australia and New Zealand most definitely should not be congratulating themselves on having ‘done better in the Covid19 pandemic’ than Sweden.

Greece

Greece is a European Union country with essentially the same population size as Sweden. It has the same pre-pandemic estimated life expectancy as the other countries charted so far (82.2), but has a significantly older population structure (pre-covid median age of 45.3), almost certainly due to a substantial depopulation of young adults in the wake of the Eurozone crisis which peaked in 2012. So we expect baseline weekly deaths to be substantially higher in Greece than in Sweden. Indeed, that is so. Pre-pandemic baseline weekly deaths in Greece stand at 2,200 compared to 1,600 in Sweden. (We note that much of this depopulation of young adults from Greece will have occurred before 2015, so we have no reason to believe that there has been a significant change in the age structure of Greece that would contribute to the pandemic-era death experience. Hence, the dominant reason for increased deaths in Greece will be Covid19.)

The chart for Greece shows no impact arising from Covid19 until October 2020. While this will be due to restrictive public health measures in the first half of 2020, it may also be due to high levels of influenza that seem to have been generally the case in southeast Europe in February 2020. This will mean that more vulnerable older Greeks will have died just before the pandemic, rather than in its early phase. And it means that Greeks will have had higher levels of general immunity in those early months.

The second European wave of Covid19, in late 2020, substantially impacted Greece, as it did all other European countries. In general, it had a disproportionate impact on vulnerable Eastern Europeans, with less natural immunity than their western co-Europeans. Greece had 11.1% more deaths in 2019‑22 compared to 2015‑18.

We see that Greece has had an unusually high level of summer epidemic death, almost certainly due to its status as a tourist destination. In 2021 Greece was a substantial victim during the ‘Delta’ outbreak; based on comparative analysis this toll was due mainly to compromised immunity (including inadequate vaccination) and not to any specifically deadly features of the ‘Delta’ variant of the Covid19 coronavirus. We see Greece with the same 50%-above-baseline mortality in December 2022 as other European countries. Southern hemisphere countries can expect this sort of peak around June 2023, though preventable by mass vaccination this April.

Chile

Chile is of interest as an alternative southern hemisphere country. It has almost exactly four times New Zealand’s population. It has a pre-pandemic baseline death rate of 1,900 which would be equivalent to 475 in New Zealand; that is, well below New Zealand’s baseline weekly death tally of 600. While this is due to Chile’s lower pre-pandemic median age (35.4 compared to Australasia’s 37.9), it also reflects Chile’s high – for the Americas – pre-pandemic life expectancy estimate of 80.2.

We see that Chile was largely successful at keeping Covid19 at bay until May 2020. But it was always more challenging in a country with land borders to three other countries, with the Peruvian and Bolivian border most significant at that stage. And clearly the international airport in Santiago was not as well sealed as those in Australasia. Unlike Australia and New Zealand, Chile was hit hard in the first half of 2021, and had a much bigger (‘Omicron’ variant) peak mortality in early 2022. Other than that, its experience in late 2021 and late 2022 was similar to Australia’s. Overall, Chile saw a 20.1% increase in mortality in 2019‑22 compared to 2015‑18, accentuated by its surprisingly low pre-pandemic base. Low pandemic mortality for South America, but high for the world as a whole. Undoubtedly Chile has also had a substantial increase in its older population, though maybe not as marked as in those countries whose birth rates were most affected by World War II.

United States

The United States is like a mix of Australia and Chile. It had a pre-pandemic estimated life expectancy of 78.9, well below both Chile and Australia; indeed a ‘third world’ life-expectancy. The median age pre-covid was 38.3, very similar to Australia and New Zealand; so having a similar age structure to the Australasian countries.

USA has a population 66 times that of New Zealand. It’s base pre-pandemic weekly mortality of 52,000 is equivalent to a high 790 for New Zealand, much higher than New Zealand’s actual 600 baseline. Given the similar age structures of United States and New Zealand, this has to be due to a generally higher pre-pandemic risk of death from all causes in the United States.

Overall, the chart for USA is comparable with the chart for Chile. Deaths in the United States increased by 16.8% over the two periods; like Chile but without the low base that might have inflated this statistic for Chile. Covid19 was clearly a big disaster for the United States, though I suspect that high levels of comorbidity – including obesity, diabetes, drug misuse, mental unwellness – contributed more than public policy. Indeed, USA had a younger profile of Covid19 mortality than most other countries.

United Kingdom

Finally, we look at the United Kingdom, with a baseline pre-pandemic death tally of 10,500 per week. That translates to 775 in New Zealand. The United Kingdom had a median age of 40.8 pre-pandemic, similar to Sweden. And a life expectancy of 81.3, similar to Finland. This older population structure largely explains Britain’s higher (than Australasia and Chile) level of baseline mortality.

Mortality patterns in the United Kingdom were most like that of Sweden, except generally higher, and significantly worse in 2021. We should also notice Britain’s huge peak in January 2023, probably partly due to Britain’s unique way of reporting death statistics. (Many late December deaths are recorded in the following year; this seems to be true for each year.)

Overall, the United Kingdom’s increase in deaths for 2019‑22 over 2015‑18 was 7.9%, same as Australia and less than New Zealand. However, we cannot claim that the demographic impact in the United Kingdom, so far, is less than in New Zealand. In the absence of the Covid19 pandemic, New Zealand’s deaths would have increased by more. This is because New Zealand’s increase in the number of people aged over 70 is more pronounced than is Britain’s. It may also be due to a worrying rate of increase in New Zealand of sub-70 non-covid mortality; that is, of mortality of people aged under 70 with American-style comorbidities. We note this already, in that the average age of people in New Zealand who die with Covid19 is significantly younger than the average age of those who die of Covid19.

Brief Conclusion

Sweden, with its more classically liberal public health approach, has had easily the lowest pandemic and post-pandemic mortality increases so far.

Data from other countries suggests that factors around general immunity and comorbidity are the major determinants of pandemic mortality; that is, neither infection rates nor viral mutation rates. And we should note that Covid19 vaccinations also probably improve general immunity, and not just immunity to the covid virus.

Re Australia and New Zealand, the lessons are two: the severe Covid19 winter of 2022/23 in (especially western) Europe will likely be replicated in Australia, New Zealand and Chile if mass revaccination does not take place this April. And that these southern countries may have unaddressed comorbidity problems, not unlike the problem in clear sight in the United States; in New Zealand this problem is by no means confined to people of Māori and Pasifika ethnicity.

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Keith Rankin (keith at rankin dot nz), trained as an economic historian, is a retired lecturer in Economics and Statistics. He lives in Auckland, New Zealand.

The first of the above charts shows excess seasonal deaths in the United Kingdom as winter approaches. While the huge mortality peaks of the pandemic in Britain are long past, we do see significant excess mortality in the United Kingdom since April. And October 2022 excess mortality rates are higher than those of 2020 and 2021. The situation in Netherlands is similar.

The story in Germany is similar, since June 2022. While the recent unseasonal mortality peak – due to Covid19 if reports are accurate – is now waning, it seems likely that Germany will face another mortality peak comparable with its influenza peak of 2016/17. In Germany, none of its Covid waves had as much peak excess mortality as the influenza peak of February/March 2018.

The data is not as up-to-date in the following three countries.

For New Zealand, we see the Covid19 deaths as a period of rising seasonal excess from February to July this year. Then there was a sharp drop-off, meaning that from August New Zealand experienced just its normal late-winter seasonal mortality. While some of this was due to Covid19, it was offset by lower-than-expected deaths from other seasonal illnesses. My hunch is that New Zealand will see a summer Covid19 mortality peak; not as high as the July peak, but unambiguously Covid19.

The other New Zealand story is the unexplained winter mortality peak of 2021. All the New Zealand public knows about this is that it was neither Covid19 nor Influenza. It might have been due in part to RSV, which hospitalised many young children in 2021. In the United States at present, we are getting reports (eg from ABC News this week) of a “tripledemic”, which includes a nasty ‘flu’ and an RSV outbreak that is hospitalising older Americans as well as children.

Finland is one country in Europe which New Zealand likes to compare itself to. Finland avoided the dramatic Covid19 peaks experienced by United Kingdom and Netherlands. But it has had worryingly high excess mortality since June 2021, and continues to do so.

Sweden, unlike Finland, had two big peaks of Covid19 mortality in 2020. Since then, Sweden has generally looked much better than all other European countries. Nevertheless, Sweden did have a problem, presumably a Covid19 problem, from June to October 2022. Though not as bad as Finland.

Overall, the pattern seems to be that populations are becoming more vulnerable to respiratory illnesses. If people who have previously had Covid19 are dying more, then damage already done by the SARS-Cov2 virus is likely to be the main culprit. If people who did not get Covid19 previously are facing a higher risk of death from respiratory illness, then the main problem is likely to be compromised general immunity arising from reduced general community contact with these types of viruses.

The post-covid mortality problem is slightly worse than it appears, especially if we consider United Kingdom and Netherlands, both countries with high early death tolls from Covid19. In these countries, many of the people most vulnerable to Covid19 have already died. So the denominator populations are, disproportionately, covid survivors (meaning either they had it and recovered, or they avoided it). Typically, after a demographically-significant epidemic, subsequent death rates should be below the historical average.

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Keith Rankin (keith at rankin dot nz), trained as an economic historian, is a retired lecturer in Economics and Statistics. He lives in Auckland, New Zealand.