COVID-19 - Middle Africa - 20-08-06

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	51104	28.4	149	0.29%	0.65%
Active cases	13548	7.5	-101	-0.74%	-0.78%
Deaths	1012	0.6	3	0.3%	0.26%
Recovered	36544	20.3	247	0.68%	1.16%

Deaths per infected	1.98%
Recovered per infected	71.51%
Active per infected	26.51%
Deaths per recovered	2.77%
Projection: Total Case Percentage	0.15%

	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	237d 9h	107d 2h
Time to reach a million cases	stable	>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:	189	Population	na
	Total cases	Cases per 100.000	Average grow rate (5 days)
Infected	na	135	105
Active	na	128	121
Deaths	na	131	99
Recovered	na	132	70
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	9309	1046	215	8048	0.49	-7.67	0.0	2.17	141d 14h		10.1	1.1	0.2	8.8	2.7	1:37.5	0.86
Cameroon	26.546	17718	2007	391	15320	0.54	6.0	0.0	0.0	129d 12h		66.7	7.6	1.5	57.7	2.5	1:39.2	0.86
Equatorial Guinea	1.358	4821	2556	83	2182	0.0	0.0	0.0	0.0			354.9	188.2	6.1	160.6	3.8	1:26.3	0.45
Congo (Brazzaville)	5.244	3546	1899	58	1589	2.16	-3.61	1.48	18.34	32d 9h	47d 3h	67.6	36.2	1.1	30.3	3.6	1:27.4	0.45
Gabon	2.173	7787	2127	51	5609	0.67	-1.18	0.4	1.45	103d 3h	173d 15h	358.4	97.9	2.3	258.2	0.9	1:109.9	0.72
Central African Republic	5.496	4620	2920	59	1641	0.03	-0.01	0.0	0.06	stable		84.1	53.1	1.1	29.9	3.6	1:27.8	0.36
Chad	15.693	942	28	76	838	0.13	-7.73	0.0	0.54	>1yr		6.0	0.2	0.5	5.3	9.1	1:11.0	0.89
Angola	31.13	1483	899	64	520	4.97	4.98	2.82	1.95	14d 6h	24d 21h	4.8	2.9	0.2	1.7	12.3	1:8.1	0.35
Sao Tome and Principe	0.2	878	66	15	797	0.09	-2.36	0.0	0.33	stable		439.0	33.0	7.5	398.5	1.9	1:53.2	0.91
Middle Africa	179.77	51104	13548	1012	36544	0.65	-0.78	0.26	1.16	107d 2h	266d 20h	28.4	7.5	0.6	20.3	2.8	1:36.1	0.72

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	9309	1046	215	8048	2.7	1:37.5	0.86	0.02	0.02	0.02	0.02	0.02	0.06	Congo (Kinshasa)
Cameroon	26.546	17718	2007	391	15320	2.5	1:39.2	0.86	0.02	0.02	0.02	0.02	0.02	0.4	Cameroon
Equatorial Guinea	1.358	4821	2556	83	2182	3.8	1:26.3	0.45	0.02	0.02	0.02	0.03	0.03	1.65	Equatorial Guinea
Congo (Brazzaville)	5.244	3546	1899	58	1589	3.6	1:27.4	0.45	0.02	0.02	0.02	0.02	0.02	0.3	Congo (Brazzaville)
Gabon	2.173	7787	2127	51	5609	0.9	1:109.9	0.72	0.01	0.01	0.01	0.01	0.01	0.63	Gabon
Central African Republic	5.496	4620	2920	59	1641	3.6	1:27.8	0.36	0.01	0.01	0.01	0.01	0.01	0.29	Central African Republic
Chad	15.693	942	28	76	838	9.1	1:11.0	0.89	0.08	0.08	0.08	0.08	0.08	0.13	Chad
Angola	31.13	1483	899	64	520	12.3	1:8.1	0.35	0.04	0.05	0.05	0.06	0.07	0.06	Angola
Sao Tome and Principe	0.2	878	66	15	797	1.9	1:53.2	0.91	0.02	0.02	0.02	0.02	0.02	2.03	Sao Tome and Principe
Middle Africa	179.77	51104	13548	1012	36544	2.8	1:36.1	0.72	0.02	0.02	0.02	0.02	0.02	0.15	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