Analysis by Keith Rankin.
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.
|Table 1: Impact of Covid19 pandemic on Mortality, Raw Data|
|*||part of Dec 2022 has been estimated|
|**||more than a month has been estimated|
|!||2015 and/or 2016 estimated|
|^||likely an undercount|
|°||has a chart here or here|
|source: ourworldindata.org/excess-mortality-covid [raw counts]|
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:
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.
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.
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.
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.
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.