COVID-19 - Middle Africa - 20-10-09

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	64134	35.7	149	0.23%	0.36%
Active cases	8909	5.0	64	0.72%	0.98%
Deaths	1305	0.7	6	0.46%	0.33%
Recovered	53920	30.0	79	0.15%	0.21%

Deaths per infected	2.03%
Recovered per infected	84.07%
Active per infected	13.89%
Deaths per recovered	2.42%
Projection: Total Case Percentage	0.2%

	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	298d 0h	192d 16h
Time to reach a million cases	stable	stable
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	145	117
Active	na	138	74
Deaths	na	142	84
Recovered	na	141	124
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	10835	317	276	10242	0.14	4.27	0.15	0.01	>1yr	>1yr	11.8	0.3	0.3	11.1	2.7	1:37.2	0.95
Cameroon	26.546	21203	663	423	20117	0.27	-2.08	0.14	0.36	260d 6h	>1yr	79.9	2.5	1.6	75.8	2.1	1:47.6	0.95
Equatorial Guinea	1.358	5063	86	83	4894	0.07	0.74	0.0	0.06	stable		372.7	6.3	6.1	360.3	1.7	1:58.8	0.97
Congo (Brazzaville)	5.244	5118	1141	90	3887	0.11	0.0	0.0	0.0	>1yr		97.6	21.8	1.7	74.1	2.3	1:43.1	0.76
Gabon	2.173	8835	592	54	8189	0.09	-2.4	0.0	0.24	stable		406.7	27.2	2.5	376.9	0.7	1:151.5	0.93
Central African Republic	5.496	4853	2877	62	1914	0.03	0.06	0.0	0.0	stable		88.3	52.3	1.1	34.8	3.2	1:30.9	0.39
Chad	15.693	1274	82	90	1102	0.92	6.25	0.69	0.43	75d 16h	100d 10h	8.1	0.5	0.6	7.0	8.2	1:12.2	0.86
Angola	31.13	6031	3134	212	2685	2.24	3.49	1.33	0.45	31d 7h	52d 9h	19.4	10.1	0.7	8.6	7.9	1:12.7	0.45
Sao Tome and Principe	0.2	922	17	15	890	0.2	9.27	0.0	0.07	352d 13h		461.0	8.5	7.5	445.0	1.7	1:59.2	0.97
Middle Africa	179.77	64134	8909	1305	53920	0.36	0.98	0.33	0.21	192d 16h	212d 2h	35.7	5.0	0.7	30.0	2.4	1:41.3	0.84

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	10835	317	276	10242	2.7	1:37.2	0.95	0.03	0.03	0.03	0.03	0.03	0.08	Congo (Kinshasa)
Cameroon	26.546	21203	663	423	20117	2.1	1:47.6	0.95	0.02	0.02	0.02	0.02	0.02	0.43	Cameroon
Equatorial Guinea	1.358	5063	86	83	4894	1.7	1:58.8	0.97	0.02	0.02	0.02	0.02	0.02	1.65	Equatorial Guinea
Congo (Brazzaville)	5.244	5118	1141	90	3887	2.3	1:43.1	0.76	0.02	0.02	0.02	0.02	0.02	0.46	Congo (Brazzaville)
Gabon	2.173	8835	592	54	8189	0.7	1:151.5	0.93	0.01	0.01	0.01	0.01	0.01	0.67	Gabon
Central African Republic	5.496	4853	2877	62	1914	3.2	1:30.9	0.39	0.01	0.01	0.01	0.01	0.01	0.3	Central African Republic
Chad	15.693	1274	82	90	1102	8.2	1:12.2	0.86	0.07	0.07	0.07	0.07	0.08	0.16	Chad
Angola	31.13	6031	3134	212	2685	7.9	1:12.7	0.45	0.04	0.04	0.04	0.04	0.05	0.18	Angola
Sao Tome and Principe	0.2	922	17	15	890	1.7	1:59.2	0.97	0.02	0.02	0.02	0.02	0.02	2.03	Sao Tome and Principe
Middle Africa	179.77	64134	8909	1305	53920	2.4	1:41.3	0.84	0.02	0.02	0.02	0.02	0.02	0.2	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