COVID-19 - Southern Africa - 20-08-02

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

	absolute	cases per 100.000	abs. development 1 day	rel. development 1 day	rel. development 5 days/average
Total infections	518076	776.8	8350	1.64%	2.18%
Active cases	160771	241.1	3348	2.13%	-1.41%
Deaths	8441	12.7	218	2.65%	2.38%
Recovered	348864	523.1	4784	1.39%	3.65%

Deaths per infected	1.63%
Recovered per infected	67.34%
Active per infected	31.03%
Deaths per recovered	2.42%
Projection: Total Case Percentage	3.42%

	Last days rate	Last average rate
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.
Time to double cases	42d 15h	32d 3h
Time to reach a million cases	40d 11h	30d 11h
Time to saturate the population	298d 23h	225d 3h

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:	189	Population	na
	Total cases	Cases per 100.000	Average grow rate (5 days)
Infected	na	21	44
Active	na	24	149
Deaths	na	31	27
Recovered	na	20	17
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:	±	±	±	±	±	±	±	±	±	±	±	±	±	±	±	±	±	±
Country	Pop (mio)	Infected	Active	Deaths	Recovered	Infected	Active	Deaths	Recovered	Infected	Deaths	Infected	Active	Deaths	Recovered	Deaths per Recovered		Recovered per infected
		absolute values				Percentage growthrate 5d				Time to double		Cases per 100.000				% / ratio
South Africa	58.775	511485	155892	8366	347227	2.16	-1.52	2.37	3.65	32d 8h	29d 12h	870.2	265.2	14.2	590.8	2.4	1:41.5	0.68
Namibia	2.459	2294	2096	11	187	3.69	2.55	6.72	12.39	19d 3h	10d 15h	93.3	85.2	0.4	7.6	5.9	1:17.0	0.08
Eswatini	1.093	2775	1518	43	1214	2.94	1.64	2.01	3.49	23d 22h	34d 18h	253.8	138.9	3.9	111.1	3.5	1:28.2	0.44
Botswana	2.25	804	739	2	63	1.76	1.93	0.0	0.0	39d 17h		35.7	32.8	0.1	2.8	3.2	1:31.5	0.08
Lesotho	2.11	718	526	19	173	7.48	7.44	3.21	6.21	9d 14h	21d 23h	34.0	24.9	0.9	8.2	11.0	1:9.1	0.24
Southern Africa	66.69	518076	160771	8441	348864	2.18	-1.41	2.38	3.65	32d 3h	29d 11h	776.8	241.1	12.7	523.1	2.4	1:41.3	0.67

More Data by Country

Click top row to sort:	±	±	±	±	±	±	±	±	±	±	±	±	±	±	±
Country	Pop (mio)	Infected	Active	Deaths	Recovered	Deaths per Recovered		Recovered per infected	Deaths per infected ... days ago					Possible Total %	Country
		absolute values				% / ratio		Recovered per infected	0d	5d	7d	10d	14d	Possible Total %
South Africa	58.775	511485	155892	8366	347227	2.4	1:41.5	0.68	0.02	0.02	0.02	0.02	0.02	3.85	South Africa
Namibia	2.459	2294	2096	11	187	5.9	1:17.0	0.08	0.0	0.01	0.01	0.01	0.01	0.12	Namibia
Eswatini	1.093	2775	1518	43	1214	3.5	1:28.2	0.44	0.02	0.02	0.02	0.02	0.02	1.06	Eswatini
Botswana	2.25	804	739	2	63	3.2	1:31.5	0.08	0.0	0.0	0.0	0.0	0.0	0.02	Botswana
Lesotho	2.11	718	526	19	173	11.0	1:9.1	0.24	0.03	0.03	0.04	0.05	0.05	0.24	Lesotho
Southern Africa	66.69	518076	160771	8441	348864	2.4	1:41.3	0.67	0.02	0.02	0.02	0.02	0.02	3.42	Southern Africa

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