Saturday, 22 May 2021

COVID-19: World Report, Omnibus Edition (Medical)

It’s been a long haul, but I have finally been through the data for all 190 countries which have reported cases of COVID-19, and assembled everything into a “master” workbook, from which I can produce spaghetti graphs, histograms, scatterplots and lots more. Here, then, is my first truly world-wide COVID status report; since last June, at any rate.

I shall confine myself today to medical data: cases, tests, deaths and vaccinations carried out. I plan to look at lockdowns world-wide in a separate report. I am also planning to address the efficacy of the vaccines a little later.

The data I am using, from Our World in Data and the Blavatnik School of Government (both at Oxford University), runs up to May 15th 2021.


Here’s the graph of cumulative cases per million world-wide:

Looking at the smoothness of the curve, I find myself thinking: First wave, second wave, third wave, what was all that about? To think of COVID-19 in those terms is to take a parochial attitude. When you look at the data for the world as a whole, you see a slight slowdown early this year; but otherwise, those numbers are still going up and up.

And 20,000 cases per million is just 2% of the population. Unless the number of recorded cases is a very serious undercount of the actual number of infections (which it certainly was in the early stages, but that’s less clear now), there are an awful lot of people still unexposed.

The daily cases (weekly averaged) are, up to scaling by population, the first derivative of the above:

The “first wave” in Europe, the Americas and the Middle East, up to May of last year, now seems like a bad dream. But it’s a bad dream that is still going on. The first sharp peak in the new year was the “second wave” in Europe, and the more recent one is India.

Now, let’s look at cases per million by country. I have a list of all 190, but it’s unwieldy. So, here are the top 20 and the bottom 20:

What do the top 20 have in common? Mostly, they’re in Europe; a lot of them in Eastern Europe. Many are relatively small countries: Andorra, Montenegro, San Marino, Luxembourg, and the Seychelles all have populations under a million. As to the bottom 20, please note the disparity of scales between the two graphs – a factor of around 150 between Georgia at the bottom of the top 20, and New Zealand at the top of the bottom 20. Here, the main factor seems to be isolation. Both in island countries, and in Africa where very few people travel internationally. And there’s something else: Chinese ethnicity. Brunei, Laos, Taiwan and Vietnam – not to mention China itself! – all have high proportions of ethnic Chinese, who might be already more familiar with this kind of virus than other races.

Lastly, a scatterplot of cases per million against the UN’s Human Development Index (HDI):

Well OK, I put in the trend line just for fun. But it’s positive. Probably because the higher the level of development, the more travel people can enjoy. If they’re allowed to.

Weekly case growth and reproduction rate

Here is the graph of the weekly case growth world-wide, and the corresponding reproduction rates (the latter are modelled data):

You can see there what happened at the beginning of the epidemic. In the middle of February 2020, both the R-rate and weekly case growth were way down. There had been a few cases outside China, but nothing much to worry about. Then all of a sudden, in the third week of February, both suddenly climbed to dizzy heights. In a paper last year, I looked at the “onset dates” – the first days when the case rates started to climb significantly – of the virus in various countries. I determined that the outbreak beyond China had begun in earnest in the period from February 19th to 21st, and started in three countries: Iran, Italy and the USA. This coincided with a wave of Chinese business people returning from China after the (prolonged by a week) Chinese New Year celebrations. In hindsight, it seems that they may have brought with them a new, and more virulent, strain than the earlier one.

All that said, it’s reassuring that R-rate and weekly case growth track each other so well; even though the weekly case growth tends to be jumpier. The virus seems to wax and wane in communicability over relatively short periods, often of one to two weeks. It’s also noticeable that the peaks and troughs in weekly case growth tend to come a few days before the peaks and troughs in R-rate. I suspect this may be because I am using centrally averaged weekly cases in my calculation, so if the R-rate is calculated over a week looking back from the day stated, this would produce an offset between the two of about half a week.


It’s so 2020 to talk about testing again! Back last spring and summer, tests were a big issue. Were they too sensitive, and over-reporting cases? And were the test numbers themselves being over-reported for political reasons?

But as I’ve said before, and say again, I’ll use the numbers I have. So, here are the top 20 countries in tests per hundred thousand:

In every one of these countries, each member of the population has had an average of more than one test. But there’s nothing much to see here. Yet.

Now, another of the metrics I look at is cumulative cases per test over the whole epidemic. Here are the worst and best performers:

Those top 20 are weird. 70% of tests in Brazil have been positive? Since the beginning of the epidemic? Now, most of the top countries in this particular hall of shame are in South and Central America. Perhaps because they were hit by the virus during the time when there was a world-wide shortage of testing kits? But there are also some Eastern Europeans there: Bosnia, Macedonia, Slovenia, to name but three.

But if you already know which countries have been doing better against the epidemic in terms of deaths per million, you will see some familiar names in the bottom 20. Norway, Finland, Iceland, Denmark. South Korea, Thailand, Singapore, Taiwan, Vietnam. Not to mention Fiji, Australia and New Zealand. And China, the source of the epidemic, at the very, very bottom.

Which countries are in both the top 20 in tests per 100,000 and the bottom 20 in cumulative cases per test? Cyprus, Slovakia, Denmark, UAE, Austria, Singapore. Having plenty of test kits available seems to lead to a lower proportion of tests giving positive results; as you’d expect. But the most successful countries of all in controlling the virus seem to have been those which have managed to hold cases per test down without doing a whole lot of testing: Norway, Finland, Iceland, South Korea, Thailand, Taiwan, Fiji, Australia, New Zealand, Vietnam, China. Add in Mongolia, Rwanda and Bhutan as unexpected wildcards, too.


Here are the daily deaths (weekly averaged) world-wide:

This time, you can see a lowering of death rates during April and May, after the “first wave” in Europe; during which, if the UK is any example to go by, the health “authorities” seem to have had almost no idea about how to treat serious cases.

After that, it follows much the same pattern as the daily cases per million, but displaced to the right by what looks like about 2 weeks. The deaths curve is also somewhat bumpier than the cases; suggesting that the lethality of the virus has a tendency to go up and down.

Here are the lists of shame and fame in terms of cumulative deaths per million, respectively:

The worst hit places according to this metric are all in Europe, and particularly in Eastern Europe. The count of shame is made up by Brazil, Peru, the USA and Mexico. And Bosnia, Macedonia and Slovenia were all in the top 20 on cases per test.

At the other end of the scale, seven countries which have reported cases have not suffered a single death. All island countries, except for the Vatican. Among those immediately above them, we see many of the same names that were in the bottom 20 in cases per test: New Zealand, Singapore, Fiji, China, Bhutan, Taiwan, Vietnam. It’s also worth noting the factor of 250 difference in cumulative deaths per million between Portugal at the bottom of the top 20 and Timor at the top of the bottom 20.

Singapore is unique in being high in tests done, low in cases per test, and low in deaths per million, all at the same time. I’ll put Singapore on my list for a specific case study a bit later.

Lastly, here’s the plot of deaths per million against UN HDI rating:

That doesn’t look so different from the corresponding plot of cases per million.

Deaths per case

Now for the deaths per case metric. Here are the graphs of cumulative deaths per case, and daily deaths per case with a 21-day offset. The first covers the whole course of the epidemic, the second from May onwards (the data for individual countries having been too noisy before that):

That suggests that there had been a “zeroth wave” in China at the end of 2019, which was on its way down in lethality by January 2020. By the end of January, it had led to a total of about 125 confirmed cases in: Australia, Cambodia, Canada, Finland, France, Germany, India, Italy, Japan, Malaysia, Nepal, the Philippines, Singapore, South Korea, Sri Lanka, Taiwan, Thailand, the UAE, the UK and the USA. Unfortunately, Our World in Data no longer includes any data on cases or deaths prior to January 22nd, meaning that I can’t analyze that zeroth wave – unless I go back and take a look at the original downloads. But the first download I took, on May 2nd 2020, had no data for China at all! There was data by May 10th, though.

The death rate began to ramp up with the arrival of the “first wave” of the virus in Iran, Italy and the USA on or about February 19th 2020; peaked in early May; and has been going gently downward ever since, apart from a small hump in March 2021. The bumps in the daily deaths per case graph suggest that the virus has actually been waxing and waning in lethality every few weeks all along; just as it does in communicability. It seems that it spawns a lot more variants than just the ones you hear about in the news! The recent drop-off may be partly an artefact of not all the data on recent deaths being in yet, or partly due to the effects of vaccines, or both.

Here are the top and bottom 20 countries on the cumulative deaths per case metric:

The people of Vanuatu have been unlucky; they have had only four cases, but one death. Yemen and Syria are war zones, Somalia is all but, and many of the other countries near the top of the deaths per case league have ongoing political problems. It’s a surprise to see Mexico right up there in third place; though their health care system does seem to have had some problems in the past. And Bosnia, Bulgaria and Hungary all have high deaths per million from relatively moderate cases per million, suggesting that they too may have health care system problems.

At the other end, though, Singapore is last of all among those that have had deaths. They surely must have been doing something right! And Mongolia, the UAE, Timor, Laos and Bhutan have all appeared at the right end of the table in some of the earlier lists.

Here’s the plot of cumulative deaths per case against UN HDI index:

The trend, such as it is, is downwards. So, the more developed countries have slightly less deaths per case; as you would expect from better health care systems.


Here’s the graph of world-wide vaccinations:

Those numbers look quite impressive. But 600,000,000 is only about 7.5% of the current world population. And many countries have not yet even started vaccinating. Here are the lists of the top 20 in people fully vaccinated (two jabs) and people vaccinated (one or two):

The Seychelles has the most vaccinated population in the world; but even they had new outbreaks early in May, resulting in the imposition of a new lockdown. But the Seychelles economy is almost entirely dependent on tourism, and some of the people infected have been visitors.

I’ll leave to another day the question of how well the vaccines are working. For today, I’ll simply identify a few countries, where we should already be able to see some significant effects of vaccinations. Israel and the UAE I think are good choices, particularly because they have similar populations of just under 10 million. And the only two large countries (bigger than 50 million) in the lists, the UK and the USA, need to be in there too.

To sum up

The seeming correlation between low cases per test and low deaths per million came as a bit of a surprise to me. But it seems to explain at least part of why some very different cultures, notably the Nordics and those of Chinese extraction, seem independently to be doing well against the virus, relative to other countries. They test early, and follow up quick.

Singapore seems to be an outstanding example of getting the virus response right. I’ll take a closer look at some time in the future. I’m not sure I believe the Chinese figures, particularly now the pre-January 22nd data has been disappeared; I’ll have to take a look at them, too. And Israel, the UAE, the UK and the USA will be on my list for looking at the effectiveness of vaccinations in a more quantitative way.


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