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
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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