COVID-19 - Middle Africa - 20-11-27

Data from JHU, ca. 9:00 CET

Middle Africa is a Group with the following members:
Angola - Cameroon - Central African Republic - Chad - Congo (Brazzaville) - Congo (Kinshasa) - Equatorial Guinea - Gabon - Sao Tome and Principe

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	79267	44.1	345	0.44%	0.42%
Active cases	12986	7.2	239	1.87%	-0.57%
Deaths	1531	0.9	2	0.13%	0.16%
Recovered	64750	36.0	104	0.16%	0.53%

Deaths per infected	1.93%
Recovered per infected	81.69%
Active per infected	16.38%
Deaths per recovered	2.36%
Projection: Total Case Percentage	0.23%

	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	158d 21h	165d 14h
Time to reach a million cases	>1yr	>1yr
Time to saturate the population	stable	stable

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:	192	Population	na
	Total cases	Cases per 100.000	Average grow rate (5 days)
Infected	na	150	126
Active	na	129	146
Deaths	na	143	110
Recovered	na	144	76
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: Middle Africa

Angola - Cameroon - Central African Republic - Chad - Congo (Brazzaville) - Congo (Kinshasa) - Equatorial Guinea - Gabon - Sao Tome and Principe

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
Congo (Kinshasa)	91.931	12470	642	333	11495	0.47	3.14	0.36	0.34	147d 3h	190d 9h	13.6	0.7	0.4	12.5	2.9	1:34.5	0.92
Cameroon	26.546	24117	1503	437	22177	0.5	9.64	0.09	0.0	139d 21h	stable	90.9	5.7	1.6	83.5	2.0	1:50.8	0.92
Equatorial Guinea	1.358	5146	56	85	5005	0.06	-2.74	0.0	0.12	stable		378.9	4.1	6.3	368.5	1.7	1:58.8	0.97
Congo (Brazzaville)	5.244	5774	692	94	4988	0.5	-13.33	0.0	5.67	137d 19h		110.1	13.2	1.8	95.1	1.9	1:53.2	0.86
Gabon	2.173	9191	95	59	9037	0.13	0.47	0.0	0.09	>1yr		423.0	4.4	2.7	416.0	0.7	1:153.8	0.98
Central African Republic	5.496	4913	2926	63	1924	0.01	0.01	0.0	0.0	stable		89.4	53.2	1.1	35.0	3.3	1:30.6	0.39
Chad	15.693	1663	63	101	1499	0.25	-1.63	0.0	0.37	272d 14h		10.6	0.4	0.6	9.6	6.7	1:14.8	0.9
Angola	31.13	15008	6969	342	7697	0.7	0.45	0.24	0.73	99d 5h	293d 9h	48.2	22.4	1.1	24.7	4.4	1:22.5	0.51
Sao Tome and Principe	0.2	985	40	17	928	0.12	0.53	0.0	0.11	>1yr		492.5	20.0	8.5	464.0	1.8	1:54.6	0.94
Middle Africa	179.77	79267	12986	1531	64750	0.42	-0.57	0.16	0.53	165d 14h	>1yr	44.1	7.2	0.9	36.0	2.4	1:42.4	0.82

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 %
Congo (Kinshasa)	91.931	12470	642	333	11495	2.9	1:34.5	0.92	0.03	0.03	0.03	0.03	0.03	0.1	Congo (Kinshasa)
Cameroon	26.546	24117	1503	437	22177	2.0	1:50.8	0.92	0.02	0.02	0.02	0.02	0.02	0.44	Cameroon
Equatorial Guinea	1.358	5146	56	85	5005	1.7	1:58.8	0.97	0.02	0.02	0.02	0.02	0.02	1.69	Equatorial Guinea
Congo (Brazzaville)	5.244	5774	692	94	4988	1.9	1:53.2	0.86	0.02	0.02	0.02	0.02	0.02	0.48	Congo (Brazzaville)
Gabon	2.173	9191	95	59	9037	0.7	1:153.8	0.98	0.01	0.01	0.01	0.01	0.01	0.73	Gabon
Central African Republic	5.496	4913	2926	63	1924	3.3	1:30.6	0.39	0.01	0.01	0.01	0.01	0.01	0.31	Central African Republic
Chad	15.693	1663	63	101	1499	6.7	1:14.8	0.9	0.06	0.06	0.06	0.06	0.06	0.17	Chad
Angola	31.13	15008	6969	342	7697	4.4	1:22.5	0.51	0.02	0.02	0.02	0.02	0.03	0.3	Angola
Sao Tome and Principe	0.2	985	40	17	928	1.8	1:54.6	0.94	0.02	0.02	0.02	0.02	0.02	2.3	Sao Tome and Principe
Middle Africa	179.77	79267	12986	1531	64750	2.4	1:42.4	0.82	0.02	0.02	0.02	0.02	0.02	0.23	Middle 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