Covid-19 Cases and Deaths by Continent (Up to the end of December 2021)

With the arrival of the Omicron variant of Covid-19, which may or may not signal the end of the pandemic, it seems like a good time to have a large-scale retrospective look at how the pandemic has developed in various parts of the world. There are many ways to categorize the world, each with their own advantages and disadvantages, but the continental scale is a fairly natural choice to make. So, that’s the unit of analysis that I will use in the graphs and text below.

Some previous blogs looked at case counts and deaths, at earlier stages in the pandemic. This blog will continue with focusing on those aspects of the pandemic. Since case counts and deaths are obviously linked, via the Case Fatality Rate, I will also look at that measure, on a continent-by-continent basis.

This will be primarily a descriptive analysis for now, at the continent level. I also have the data categorized by Hemisphere (north/south) and Latitude Range (high, medium, low); I will reserve those for a later blog, so as to not make the blog too long.

Later I will try some regression analysis to see which of the variables that I have (or can get) correlate with outcomes of interest, such as case counts and deaths. I will also try some cluster analysis (groups with similarity), to see if there are natural clusters in the data, and how well the assumed categories such as continents and latitude correspond to those possible natural clusters.

On occasion, I will keep make note of some of my earlier comments in this update. They sometimes demonstrate how difficult it was/is to predict the gyrations of the pandemic’s course.

A Note on Data

As many people have noted throughout the pandemic period, there have always been some issues with regard to data reliability in the Covid-19 reporting. Some of those issues include:

How were cases determined, and what proportion of infections were actually reported as cases? Who was tested and how were the tests done? How did that vary throughout the world? Were rolling random samples tested, or were tests only initiated by medical visits? How about water-treatment plant tests?
How were Covid-related hospitalizations counted? What proportion of these hospitalizations were primarily due to Covid-19, and how many were essentially incidental (for example, a person goes to the hospital with a broken leg, but is then tested positive for Covid).
How were Covid-related deaths counted? As with hospitalizations, how many Covid-related deaths were incidental, As an example, I knew one person who died of cancer in hospital during the early days of the pandemic, that was swabbed and tested within a half-hour of his cancer-related death. It turned out that he tested negative, but had he tested positive, by the protocols of the time he would have been called a Covid-related death.

The rise of the Omicron variant has brought more transparency to these issues. For example, in the December 30, 2021 issue of the Toronto Globe and Mail (a very mainstream source) we can read statements such as the following:

The scientific director of Ontario’s Covid-19 Science Advisory Table, Peter Juni, estimates that the province’s daily count is now capturing just one case out of every five to eight cases in the province.
The daily measurement has always had flaws. For one, it almost exclusively records cases that have been confirmed during lab-based polymerase chain reaction (or PCR) testing. In the past, when the demand for tests outstripped the capacity of labs, such as during the virus’s deadly first wave, many people who suspected they were infected couldn't get tested, causing government tallies to under-count the spread of the virus.
In Ontario, even before Omicron came along, case counts only captured about two out of very five Covid-19 inflections according to Dr. Juni – a ratio verified by mortality data and serological testing.

Similar statements are coming out regarding incidental hospitalizations and deaths. In my opinion, it is still useful to look at trends, but the possibilities for over-counting and under-counting should be kept in mind.

Aggregate Cases and Deaths, up to End of 2021

1 - Raw Numbers of Aggregate Cases and Deaths

The graphs below show aggregate case counts and deaths, for the various continents at different points in time. Note that the graphs have not been normalized for population or any other relevant factors, they just show the raw totals for cases and deaths. Further on, they will be normalized by population.

The first graph indicates that Europe has had the highest number of cases, over the two years of the pandemic, though only slightly higher than Asia. North America is at about two-thirds the level of Europe and Asia, and South America has about half the number of cases of the two highest continents. Africa and Australasia are far down the graph, with relatively few cases.

As for Covid-related deaths, the second graph shows that Europe is still highest, with Asia, North American and South America in a close cluster, at about four-fifths the level of Europe. Again, Africa and Australasian are far down the graph, though Africa has opened up some space on Australasia.

Obviously, these comparisons, interesting as they are, need to be normalized for population, which I will do a little later on in this blog.

Here is a comment that I made in an earlier blog on this subject, in the spring/summer of 2001:

The classic sigmoid, or S-shapted curves, of Europe and North America indicate that the pandemic is near its end in those areas, short of a new variant that is not affected by the current vaccines. This appears to apply to both cases and deaths. At this point the new variants appear to be under control, via the vaccinations, with severe outcomes such as death particularly well controlled by the vaccines.

It was true then; these two continents did show a classic sigmoid functional shape, until autumn of 2001, when the Delta variant showed up. But you can see how the graphs took off in the fall and winter of 2001, a good example of how natural selection can throw a spanner into the works, when it comes to predictions of the course of a pandemic. The Omicron variant is now continuing to throw predictions into confusion, with cases rising quickly in December 2021, but deaths rising more slowly.

As always, it should be noted that there is a good deal of uncertainty in these numbers, due to differences in reporting standards and levels of economic development.

2 - Aggregate Cases and Deaths per Million Population

Case and death counts alone don’t tell the whole story. Naturally regions with larger populations will experience higher case counts and deaths, other things being equal. But the evidence shows that not all things are equal. When an adjustment for population is made (expressing the data as Cases per Million Population and Deaths per Million Population), things are quite different:

The case count data appears to break into two main groups:

South America/North America/Europe are in a high case count per million group. The December 2021 data shows that Europe and North America had large surges in cases, while South America did not. That is a good indication that Omicron had taken hold in Europe and North America, but hadn’t yet become prominent in South America. The time lag is likely due to the higher levels of travel and other globalization factors in North America and Europe.
Asia/Africa/Australasia are in a relatively low case count per million group. However, Australasia has begun to see a noticeable uptick in cases in December 2021, relative to the other two.

The deaths count data are similar:
- South America/North America/Europe are in a high deaths per million group, though it could be argued that South America has actually broken far enough from that group to constitute a “very high group” all on its own. That said, deaths were trending up more quickly in Europe/North America in the December 2021 data. It is not clear whether that is Omicron or the last catch-up in deaths due to the Delta variant.
- Asia/Africa/Australasia are in a low deaths per million group. Asia is now more firmly in the low deaths group than it was in the low case count group. Deaths in Australasia have not yet shown the uptick that was seen in cases.
The members of the high group had quite similar case count trajectories, until spring of 2021, when the European and North American count increase decelerated, while the South American case count continued on a linear path. This was also true of deaths, though the South America death count graph is much steeper than the case count graph. But by the fall of 2021 these trends reversed, with Europe and North America accelerating and South America decelerating.
As noted, Asia appears to have broken away from the low case group, but that trend is not so obvious for the low death count group.
Africa and Australasia have both maintained low trajectories, though Australasia has overtaken Africa in cases per million population but not in deaths per million.

Case Count and Deaths by Time Periods up to End of 2021

3 - Raw Numbers per Time Interval

Here are a couple of graphs, looking at case counts and deaths during particular intervals. The intervals are mostly months, though in the earlier period they are sometimes longer. The graphs are little “busy”, but that is just how the analysis of data can be sometimes. Here are some observations, to help in interpreting the graphs:

In terms of cases, Asia was hit early, peaking in late 2020, it then experienced a decline which was interrupted by new waves in spring and fall of 2021(these waves have been give the names Alpha, Beta and Delta). The Omicron wave of late 2021 does not appear to show up in the graph for Asia.
Europe was also hit early, plateaued for a while, then rose quickly and peaked in early 2021. It then came down steadily, but was hit by another wave in summer 2021. It then grew steadily, hitting a maximum at the end of 2021. This final phase is likely a combination of the end of delta and the start of Omicron.
North America had numbers similar to Asia at the start, but then shot up in a similar matter to Europe, peaked in early 2021 and fell off thereafter. The early death counts were also unusually high, at least compared to Asia. It then got hit by the Delta wave in summer/fall of 2021, came down from that, and was finally hit by Omicron at the end of 2021.
South America’s path was similar, following the Alpha, Beta, Delta path. However it was somewhat out of phase with other continents, due to its location, straddling the northern and southern hemispheres.. It had quite high numbers during these waves, but those had tapered off by the end of 2021. This data does not yet show an Omicron wave in that region.
Africa remained at relatively low case levels for the duration, though there is a detectable Alpha/Beta/Gamma pattern, which is rather similar to South America, but more subdued. There is a detectable uptick late in 2021, corresponding to the Omicron outbreak in southern Africa.
Australasia’s case count barely shows up at this scale, a result of both low counts and a low population. However, there is a slight rise visible by December 2021, with the appearance of Omicron.

In terms of deaths, Asia’s experience was quite similar to its experience with cases, as would generally be expected. It was hit early, peaked in late 2020. declined, then peaked again during the two new waves in spring and fall of 2021. As with cases, the Omicron wave of late 2021 does not appear to show up in the graph.
Europe experienced a large number of deaths immediately, then fell to low death counts, was hit hard by the Beta wave of late 2020, fell again, and was hit by the Delta wave in the latter part of 2021, though that latter wave didn’t result in as many deaths as the Beta wave. It doesn’t seem to have had many deaths from Omicron, which seems to be a feature of the latter variant.
South America experienced its greatest death counts in the fall of 2020 and the fall of 2021. Of course, for most of South America those would be spring, rather than fall. As with other regions, Omicron does not seem to have resulted in many deaths.
Africa’s death counts generally mirror its case counts, as far as the shape of the graph goes, showing 3 significant waves. Omicron showed an increase in cases, but there is no corresponding increase in deaths.
As with cases, the graph for deaths in Australasia is quite flat. Deaths do not show the slight uptick that cases do, at the end of 2021.

4 - Case Counts and Deaths per Day per Million Population per Time Interval

As with the aggregate counts, expressing the time interval data (mostly months) as Cases per Million Population per Day brings out some very different aspects of the world-wide pandemic. Since the time periods in the graph were not equal in duration, this normalizes them to a “per day” basis. Similarly, since the continents are not equal in population, this normalizes them to a “per million population” basis. So, for purposes of comparison, this is the preferred graph.

Some comments to aid interpretation:

Asia actually had rather low case counts per million population per day for most of the pandemic period. The number drifted upwards after spring 2021, before heading back down in the latter part of 2021.
Europe really got hit quite badly overall, but the really big pandemic didn’t start until autumn 2020. It then exploded, peaked in early 2021 and fell off steadily throughout 2021, to relatively low levels. But then Delta hit hard, and cases per million people went back up, to eventually far exceed the previous high levels.
North America had an experience broadly similar to Europe, though it did get hit earlier, peaked at a higher rate, then fell off more quickly. Its Delta wave appears to have hit somewhat earlier than in Europe, the subsided. It also had a sharp increase at the end of 2021, with the arrival of the Omicron variant.
South America went through two main peaks, including an extremely high peak in July 2021 (this was winter in much of South America). Cases per million then fell off sharply, to relatively low levels.
Africa has not been hit very hard at all, relative to the other continents, though there were detectable waves in early and late 2021.
Australasia had very low cases per million population, until well into 2021. It saw a very sharp increase in the last month of 2021, as Omicron hit the region.

In terms of Deaths per Day per Million Population, Asia tended to be quite low overall. However, it did see higher levels in 2021 compared to 2020
Europe had rather high levels of deaths per million during several intervals, particularly the winter and spring of 2020-21. Numbers then fell substantially, but went back up in late 2021, with the Delta variant.
North America saw a peak from the autumn of 2020 to the spring of 2021. Deaths per million then fell until the arrival of Delta in fall 2021. By winter 2021, deaths per million were trending down, with only a small uptick in December.
South America had an early peak around September 2020. Deaths per million then dropped, until April 2021, when they began an extreme rise, peaking in July 2021 at the highest rates seen around the world. After than, rates fell to low levels.
Both Africa and Australasia had low deaths per million throughout the pandemic period, though they were somewhat higher in 2021 than 2020. Australasia’s uptick in cases per million in late 2021 has not been matched by a corresponding increase in deaths per million.

5 - Case Fatality Rates by Continent and Time Periods

Of particular interest is the trajectory of the Case Fatality Rates (CFR) for different areas of the world. I have defined this as (Deaths/Cases). Deaths generally lag cases by about 2 weeks, as it takes some time for the disease to progress to the end-point of death; however at this scale it seems reasonable to ignore the time lag.

The data is shown in the two associated graphs. The first graph shows the trend in the aggregated Case Fatality Rates for the various regions over the two years of the pandemic. In other words, at each time step all of the cases and all of the deaths up to that point in time are used for the calculation. The second graph shows the trend in the Case Fatality Rates for each time interval for the various regions over the two years of the pandemic. In other words, at each time step all of the cases and all of the deaths that occurred during that time interval are used for the calculation.

Here are some observations:

The general trend in the first graph was clear: Case Fatality Rates were high at the start of the pandemic (mostly about 3 to 6 percent), dropped quite quickly (to about 1to 3 percent), then remained fairly stable, though there was some variation in the latter time intervals. South America, in particular, had aggregate rates rise in the latter half of the time period, due to its extremely serious wave during mid-2021

The second graph, showing Case Fatality Rates specific to the various time intervals shows a fair bit of variation. There are some periods where the CFR goes up in some regions, in other time intervals it goes down.

As noted, the mid-2021 (i.e. around 2021/07/01) Beta wave was quite severe in many regions, as measured by the CFR. However, it quickly dropped, possibly due to rising vaccination rates helping to reduce severe effects in a high proportion of cases.
The late 2021 Delta wave also resulted in a higher CFR in some regions, notably Africa and North America.
In most regions, the CFR drops in the final interval. This is partially an artifact of the lag in reporting of deaths, but is also indicative of the reduced severity of the Omicron variant.
The initially high rates might also be an artifact of reporting. At the beginning it was easier to identify deaths than cases (until widespread testing became available).
This may have also been at least partially responsible for the apparent increase in CFR in some of the other waves. As cases tended to rise rapidly, the ability of medical systems to maintain testing levels may have been exceeded. Presumably, accurately establishing Covid-related deaths was not as affected by sudden outbreaks. That said, these are issues that we can’t be certain of, barring some later medical sleuthing of hospital records and such.
Similarly, the drop off in CFR during some periods may be due to improvements in treatments that developed as medical systems gained experience during the pandemic. This has been seen in many previous pandemics in history.
Past pandemics have tended to see reductions in severe outcomes as time goes on, though often rates of infection increase at the same time. Evolution experts explain this as a natural result of the disease organism adapting to the host, as the host adapts to the organism (i.e. the disease organism doesn’t really “want” to kill the host, it would rather coexist).
There is still some controversy over this hypothesis. However, the course of the Omicron variant seems to be supporting this theory.

Summary Comments (updated with December 2021)

Here are a few observations that seemed to be of the most interest:

Highly Impacted Regions vs Relatively Low Impacted Regions

The graphs in Section 2, Aggregate Cases and Deaths per Million Population show a very obvious divergence between areas that have high infection and death rates from Covid-19 (Europe, North America, South America) and those with relatively low rates (Asia, Africa, Australasia), once the data was adjusted for population. This divergence widened with time.
This is probably somewhat contrary to many peoples intuition, especially the idea that Asia doesn’t seem to have been that hard hit. That is probably because various regions in Asia have been “hot spots”, which make dramatic TV and news reports, and thus have had a lot of media exposure.
Also, the disease (apparently) began in Asia, so there may be a psychological anchoring effect, whereby the originating location is always “top of mind”. For example, the data indicates that China has experienced a relatively low impact from Covid (in terms of cases and deaths, though not necessarily different types of social disruption), yet many people probably assume that China has actually been severely affected by the pandemic.

South America Hit Hard

On the other hand, South America’s very high infection and death rates, relative to population, is likely to surprise many people. This is probably due to South America’s fairly peripheral geographical, cultural and media position in the world – it just tends to be overlooked. Fortunately, South America’s severe outbreak of mid-2021 tapered off towards the end of that year.

Old World vs New World

In some ways this looks strikingly like an “Old World” vs “New World” effect. Perhaps it reflects the fact that populations in the New World had less exposure to the virus or to some precursor virus that gave relative immunity to the Old World populations. However, the inclusion of Europe in the new world group and Australasia in the old world group cloud that picture. It is noteworthy that this divergence is greater for deaths than for cases, which might be expected if some type of differential natural immunity is playing a role.
This may also be due to cultural and technical differences in reporting practices. North America, South America and Europe may be better equipped to keep the necessary records and may have been under more scrutiny by the public to do so, given that most of these countries currently have relatively democratic governments.

East vs West

The other possibility is an East vs West effect. In that case, any precursor virus might have given some immunity to those in the eastern part of Eurasia but not in the western part or in the New World. The Caucasus mountain ranges do present a fairly formidable natural barrier. Again, the divergence is greater for deaths than cases, which might be expected if some type of differential natural immunity is playing a role.
Again, this may be primarily due to technical and cultural differences among world regions.

Levels of Globalization and the Pandemic

It could also represent a split between highly globalized parts of the world (in the sense of large scale tourism, business travel and migration) and less globalized parts. That has some merit, though one doesn’t necessarily think of South America as being more highly globalized than Asia. Nonetheless, there is a lot of north-south migration within the Americas, which could be a significant vector for the pandemic.
The timing of events does tend to support the globalization hypothesis, with Asia (apparently the originating region) being hit first though not all that hard, then the virus spreading to the highly globalized regions of Europe and North America (where it had a much greater effect) and finally slowly spreading to South America. The upticks in Africa and Australasia (relatively isolated regions) are consistent with that hypothesis, though they are still far too small to be definitive.
The most recent month’s data show a continuing uptick in Africa and Australasia, which would tend to support the globalization hypothesis. It could be said that these regions were “late to the party”, due to their relative geographic and/or economic isolation from the epicentres of globalization.

Genetics

There may be some sort of genetic effect at work, as it seems to have hit areas with significant Indo-European populations hardest of all. However, within these regions, there were no strong genetic differences between ancestry groups, as far as I know.
The differences that do exist between different ancestry groups in these regions can also be explained by differential vaccination rates within the various countries.
Again, the recent increases in Covid in Africa and Australasia would tend to support the idea that most or all of the world’s major population groups are quite susceptible to the virus, though we can’t dismiss the possibility that some populations are more susceptible than others.

Late Drop in Case Fatality Rates and the Omicron Variant

As noted earlier, most regions see a drop in CFR late in 2021. This is consistent with research indicating that the Omicron variant may be much less severe than earlier variants, such as Delta.

Vaccinations, Mutations and Severity of Covid-19

Following the progress of the pandemic, it became very clear that the virus was extremely quick to mutate to new forms.
For example, in many areas case counts were dropping as vaccination rates grew during 2021. The Delta variant was capable of sometimes evading the vaccine effect and this became very pronounced with the Omicron variant. That showed up in the case and death data.
Fortunately, this was usually associated with lowered severity of the disease. This may be a combined effect of intrinsically less severe disease and population’s whose immunity had been raised considerably by vaccination and previous infection.
There is great hope that the virus may now be mutating to the endemic, rather than pandemic state. However, it has been a wily opponent for the human race, so it may still have surprises in store.

Sources:

The Globe and Mail

https://www.worldometers.info/coronavirus/#countries

https://github.com/owid/covid-19-data/tree/master/public/data/vaccinations

Some earlier Covid-19 blogs:

https://dodecahedronbooks.blogspot.com/2021/07/covid-19-cases-and-deaths-by-continent.html

https://dodecahedronbooks.blogspot.com/2021/07/covid-19-cases-by-continent-jan-2000-to.html

https://dodecahedronbooks.blogspot.com/2021/03/covid-19-vaccines-how-successfully-are.html

https://dodecahedronbooks.blogspot.com/2020/12/covid-19-vaccines-comparison-of.html

https://dodecahedronbooks.blogspot.com/2020/09/covid-19-continues-to-travel-around.html

https://dodecahedronbooks.blogspot.com/2020/07/has-covid-19-become-less-deadly.html

https://dodecahedronbooks.blogspot.com/2020/07/july-2020-update-covid-19-death-rates.html

https://dodecahedronbooks.blogspot.com/2020/05/covid-19-death-rates-correlate-highly.html

https://dodecahedronbooks.blogspot.com/2020/06/covid-19-impact-on-employment-no-impact.html

https://dodecahedronbooks.blogspot.com/2020/04/is-there-model-that-can-predict-when-to.html

https://dodecahedronbooks.blogspot.com/2020/03/estimating-fatality-rate-of-coronavirus.html

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