COVID-19 - Southern Africa - 20-06-06

Data from JHU, ca. 9:00 CET

Southern Africa is a Group with the following members:
Botswana - Eswatini - Lesotho - Namibia - South Africa

Go to the data tables


absolutecases per 100.000 abs. development
1 day
rel. development
1 day
rel. development
5 days/average
Total infections 46368 69.5 2560 5.84% 5.97%
Active cases 20889 31.3 1343 6.87% 3.51%
Deaths 956 1.4 44 4.82% 5.2%
Recovered 2452336.811735.02%5.96%
Deaths per infected 2.06%
Recovered per infected52.89%
Active per infected 45.05%
Deaths per recovered 3.9%
Projection:
Total Case Percentage
0.39%

Gives the time necessary to double the existing infections - to reach a million from the existing status, or to reach the population limit of the given group (which can well be below a million). This assumes the exponential growrate of the last day or average of the last five days continues - which it does not, as there will be saturation towards the maximum. Please take these calulations with two grains of salt. As long as there is turning point in sight the data may well hold, though.
Last days rate Last average rate
Time to double cases 12d 4h 11d 22h
Time to reach a million cases 54d 1h52d 22h
Time to saturate the population128d 0h 125d 9h

A ranking may taste a bit fishy, as this is not a competition between countries, but to compare the relative efficiency of measures taken, or for detecting which countries are likely to get critical next, this ranking imho deserves a place in this overview.
Total: 189Population na
Total casesCases per 100.000Average grow rate (5 days)
Infected na 64 17
Active na 48 38
Deaths na 74 15
Recovered na 62 16
The ranking is made over all groups and countries, including small or recent that are ommitted in the table on the front page - which may lead to minor discrepancies between both!

Diagrams

Members of Group: Southern Africa

Botswana - Eswatini - Lesotho - Namibia - South Africa

Data by Country


Click on the header to sort - Click on the name for the countries dashboard! - Only countries with more then 100 infections and more then 100.000 citizens are listed!
Click top row to sort:±±±±±±±±±±±±±±±±±±
CountryPop (mio)InfectedActiveDeathsRecoveredInfectedActiveDeathsRecoveredInfectedDeathsInfectedActiveDeathsRecoveredDeaths per RecoveredRecovered per
infected
absolute valuesPercentage growthrate 5dTime to doubleCases per 100.000% / ratio
South Africa58.7754597320763952242586.013.555.236.011d 21h13d 14h78.235.31.641.33.91:25.50.53
Eswatini1.0933229532241.92-3.080.02.7136d 9h29.58.70.320.51.31:74.60.7
Southern Africa66.694636820889956245235.973.515.25.9611d 22h13d 16h69.531.31.436.83.91:25.60.53

More Data by Country

Click top row to sort:±±±±±±±±±±±±±±±
CountryPop (mio)InfectedActiveDeathsRecoveredDeaths per RecoveredRecovered per
infected
Deaths per infected ... days agoPossible
Total %
Country
absolute values% / ratio0d5d7d10d14d
South Africa58.7754597320763952242583.91:25.50.530.020.030.030.030.040.44South Africa
Eswatini1.0933229532241.31:74.60.70.010.010.010.010.010.07Eswatini
Southern Africa66.694636820889956245233.91:25.60.530.020.030.030.030.040.39Southern Africa

Heinsberg study

A study of the University of Bonn on the spread of Covid-19 at Heinsberg - the most affected county in Germany - showed a rate of deaths to infected of 0.37%. As this is the first reliable data on this ratio I use it as a projection from the number of reported deaths to the spread of the disease in the whole population, given as percentage. Note that locally other factors, like a developing spread, unreported deaths or a situation where people are more prone to die due to an overstretch of the health system will affect this number. Countries with a different population structure (eg. more young vs. old) may also get other ratios, so take this with a grain of salt - I will keep an eye on the developing scientific results.
Links (German):
Preliminary results - Press coverage: Die Welt