Coronavirus deaths


Although this page may not be updated every day, most of the graphs are updated at least every second day. Do check back regularly to view the graphs (a page refresh may be required, which is F5 for most browsers). Latest update 8 January 2020.

I made a major update to this page on 18 October, I have changed several things since I started it in April..

One of the most interesting things about this whole coronavirus epidemic, to me, is how the media (and the clever people) like to use stats. One of the most bandied about statistic is the number of tests done. From this, the theory is to trace recent contacts of anyone found to have the virus and then to test these contacts. Of course, what is supposed to follow from that is that everyone who has the virus is supposed to "self-isolate" for at least two weeks in order to prevent further spread of the virus.

The clever people now make all kinds of guesses from these numbers as to what is happening, and then what is going to happen. Unfortunately, the only thing they have right is that the virus is going to spread, and there is nothing we can do about it. There is much hype about a vaccine that is going to stop the general population from getting the virus, but as yet, there is no vaccine for the common cold nor the annual flu, so what are the chances of a vaccine for the coronavirus being discovered? As things stand at the moment, there are only two ways out after contracting the coronavirus: you recover because your immune system can overcome the disease; or you die. There is no medical cure.

There is much hype around slowing the virus to prevent overloading of the health care system (the buzzword is flattening the curve), but I have not heard a single word from any reporter, government spokesperson, nor clever person, as to why the health systems cannot handle serious cases. The answer to this is simple, money that should have gone to health care was spent elsewhere.

The unfortunate issue with this virus is that many people ending up in a hospital are more than likely terminal, so will probably die.

Because of what I have said above, I believe the most important stat that should be monitored is how many people are dying in a population. The total number of cases in a population is meaningless as it stands at the moment as it is impossible to test a whole population - there is no money nor facilities to do this job. South Korea had the facilities in place before the virus started, so was able to stop carriers very early in the epidemic. China seems to have gotten it right by brute force, but the rest of the world, by and large, got left behind.

The following is a series of charts of the daily deaths per million population in a few countries I have followed. The reason for using deaths per million is so that a comparison can be drawn between different countries. Without this, comparing countries like India (1353 million population) with Portugal (10.3 million population) would result in a rather skewed view of the numbers: India 110617 deaths and Portugal 2110 deaths (14 October). However, if one looks at this relative to the size of the population of the countries, India has had 81.7 deaths per million population and Portugal 204.8 deaths per million. As we can now compare these numbers, we see that Portugal is far worse off than India.

Another point is what do we monitor? Total deaths or daily deaths? Total deaths is rather a poor indicator, as one is unable to see the turning point in the numbers on the typical sigmoid curve which is followed by a disease. This peak can easily be seen on a differentiated curve. In order to do this it is necessary to calculate the daily deaths from Worldometer's daily total deaths. This is what I have used in populating the graphs below. [Unfortunately, Worldometer's numbers change as the various countries update their counting methods - this leads to hideous spikes and dips in the numbers I have been collecting.] Regardless of these changes, the daily death rate seems to follow the curve prior to the change, regardless of whether the total death count is modified up or down. A case in point is the UK data. I have manipulated their data on two occasions, to minimise the effect of the spike introduced on 30 April (UK data adjustments), yet the trend (deaths per day) has not changed.

These charts should be updated regularly (unless I too succumb to the virus).

Plotting the number of daily deaths, calculated from the data given on Worldometer, results in a wildly varying graph as shown in fig 1.

Fig 1. Daily coronavirus deaths per million population of some countries in the northern hemisphere

As you can see, there is a large amount of scatter on the daily tallies on the graph above. In order to smooth the curves somewhat I have taken a five day moving average on the data. The average value is placed on the middle day of the set being averaged (thanks to Prof Niko Sauer for the idea).

Fig 2. Five day moving average of the daily coronavirus deaths per million population of some countries in the northern hemisphere

Unfortunately, as the daily deaths decreased and the curves merged, it became difficult to resolve the changes expected after the surge in infections in Europe during September. As a result, I have split the countries I have been monitoring onto separate graphs.

Some southern European countries.

Fig 4. Five day moving average of the daily coronavirus deaths per million population of some southern European countries

Comparing fig 4 to fig 2, you can now see an increase in the daily number of deaths in these countries in October, which was partially masked in fig 2.

The second wave of infections currently occurring in the northern hemisphere does not appear to be as deadly as the one from March. I have looked at the figures from Spain as it was the first European country to be hit a second time.

Italy has been especially hard hit during the second wave. (17 December 2020)

Of the countries I have been monitoring, Spain and Italy were the first to pass 1000 deaths per million population during the second wave.

Some northern European countries.

Fig 5. Some northern European countries and the UK

What was quite interesting in fig 5 is that Sweden did seem to be better off than most other countries, after the disease settled down. It also does not seem to be following the European trend of an increasing death rate in late September and early October (15 October). Sweden had a horrific spike in deaths on 10 December. Also, their pathologists (or whoever reports their death numbers), definitely don't seem to work from Saturday to the following Tuesday. After this rest period, their numbers usually change quite radically from what was presented during the previous week. There is usually no correlation between numbers before their "recess" to when they restart updating data. As a result, I am going to stop updating the Swedish results from 19 December (their next "recess"). I am afraid they took the matter out of my hands. On 18 December their numbers for 17 December changed from 7802 total deaths to 7870 for the same day. Charting the numbers as I do, this looks like a massive daily spike for a country with a small population like Sweden. From the UK numbers, I have found that these modifications to the counting method makes absolutely no difference in the rate of deaths - this is the number the clever people should be monitoring, not the counting method. (18 December 2020)

The UK's numbers did follow the European trend of the second wave, with a spike in late September/early October. Their daily deaths have maintained the same rate in spite of their changes to the way they count the deaths on two occasions. They do seem to have passed the peak in the second wave, but time will tell. (17 December 2020)

Russia's curve was rather strange as it did not seem to be following the pattern of other European countries I am monitoring. However, their death rate numbers did seem to follow the second wave spike experienced in the other countries. (17 December 2020).

The Americas

One of the countries I was interested in was the USA. For completeness, I decided to follow the northern and southern neighbours as well. As Brazil, like Sweden, was also following a hands-off policy towards the virus, I included them.

Fig 6. Some countries from the Americas

As you can see from the curves, Mexico and Brazil are following pretty much identical death rates. Of all the countries I have been following, this has to be the strangest coincidence I have seen. Currently, the USA is worse off than Mexico and Brazil.

The second wave of deaths in the USA can almost certainly be attributed to the riots following George Floyd's death.

Other countries

As I am most interested in South Africa, this has to be included! Iran is included as it was one of the first countries to be hit by the disease. India is included for the sheer size of its population, and the widely differing social standings of the population.

At the start of the epidemic, I was also recording China, South Korea and Australia. However, these countries stopped producing interesting data very early on in this exercise, so I stopped monitoring them.

Fig 7. Iran, South Africa and India

Iran has the strangest curve of any country I have been following. The deaths were decreasing after their initial outbreak, but then after Ramadan started increasing drastically again. This peaked around 28 July and decreased for about month, when a third wave started. I would be very interested to know the reason for this third wave.

India is also an interesting case as the death rate due to the virus is remarkably low. They seem to have finally peaked around 20 September.

South Africa had one of the strictest government enforced lockdowns in the world. This included a curfew, a total prohibition on the sale of alcohol and tobacco products, and a total shutdown of international travel. Although there were a large number of infections, the death rate remained very low. The curve followed very much the same trend, and severity, as Canada (see fig 6).

On 6 January 2021, an announcement on the South African Covid-19 update webpage said that 884 deaths had been reported. However, 452 of these deaths were due to "data reconciliation" from May to November 2020. In order to prevent a massive spike on the graph, I have spread these 452 deaths over the period of the second wave in South Africa (29 November 2020 to 6 January 2021) as it would really require a lot of effort to correct all the data from May to 6 January.

The 452 deaths reported from the Eastern Cape are as a result of data reconciliation dating between May and November 2020- this includes analysis of community cases where post-mortem swabs were taken for COVID testing and analysis of clinical records where the the diagnosis was unconfirmed at the time of demise. The National Department of Health is engaging the province to investigate the details of the reporting backlog.

(updated: 7 January 2020)

The media often misleads the public as to the vulnerable age for the virus. This is often touted as being between 60 and 69 - this is not true.

The second wave has hit South Africa. Niko predicted this on 4 December, before the decision makers did - it's a pity that these decision makers rely on non-scientists to assist them in making their decisions.

His graph shows positive infections per number of tests.

Fig 8. Second wave of infections in South Africa (4 December 2020)

His word were, things do not look good.

Although the death rate does not show quite the same rate of increase as shown in Figure 8, you can see from Figure 7, there is an upturn (10 December).

This has changed, as you can see from Figure 7, the upturn in the death rate looks serious. What is worrying, is the number of people going on holiday, to visit family, in areas that are now designated coronavirus hotspots in South Africa. These people will be returning to their homes in the new year. A new spreader event is in the offing.

The second wave of infections is now looking really bad, as is the death rate shown in figure 7.

Fig 9. Second wave of infections in South Africa (30 December 2020)

(updated: 8 January 2021)


1: I started the data collection on 23 April 2020.

2: For consistency, I try to collect the data daily between 09:00 and 11:00 SAST (GMT+2).


The population numbers were taken from Google on 23 April 2020

The deaths per country is from Worldometer. Worldometer does have a table filled with various numbers relating to the coronavirus for the whole world, including deaths per million. However, I was interested in a much smaller subset.

Data preceding 23 April 2020 was collected off Worldometer's daily death graphs for each country shown above. I could find no other way to access this data.

(updated: 4 December 2020)