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


absolutecases 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 3654420.32470.68%1.16%
Deaths per infected 1.98%
Recovered per infected71.51%
Active per infected 26.51%
Deaths per recovered 2.77%
Projection:
Total Case Percentage
0.15%

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 237d 9h 107d 2h
Time to reach a million cases stable>1yr
Time to saturate the populationstable 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: 189Population na
Total casesCases per 100.000Average 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:±±±±±±±±±±±±±±±±±±
CountryPop (mio)InfectedActiveDeathsRecoveredInfectedActiveDeathsRecoveredInfectedDeathsInfectedActiveDeathsRecoveredDeaths per RecoveredRecovered per
infected
absolute valuesPercentage growthrate 5dTime to doubleCases per 100.000% / ratio
Congo (Kinshasa)91.9319309104621580480.49-7.670.02.17141d 14h10.11.10.28.82.71:37.50.86
Cameroon26.546177182007391153200.546.00.00.0129d 12h66.77.61.557.72.51:39.20.86
Equatorial Guinea1.358482125568321820.00.00.00.0354.9188.26.1160.63.81:26.30.45
Congo (Brazzaville)5.244354618995815892.16-3.611.4818.3432d 9h47d 3h67.636.21.130.33.61:27.40.45
Gabon2.173778721275156090.67-1.180.41.45103d 3h173d 15h358.497.92.3258.20.91:109.90.72
Central African Republic5.496462029205916410.03-0.010.00.06stable84.153.11.129.93.61:27.80.36
Chad15.69394228768380.13-7.730.00.54>1yr6.00.20.55.39.11:11.00.89
Angola31.131483899645204.974.982.821.9514d 6h24d 21h4.82.90.21.712.31:8.10.35
Sao Tome and Principe0.287866157970.09-2.360.00.33stable439.033.07.5398.51.91:53.20.91
Middle Africa179.7751104135481012365440.65-0.780.261.16107d 2h266d 20h28.47.50.620.32.81:36.10.72

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
Congo (Kinshasa)91.9319309104621580482.71:37.50.860.020.020.020.020.020.06Congo (Kinshasa)
Cameroon26.546177182007391153202.51:39.20.860.020.020.020.020.020.4Cameroon
Equatorial Guinea1.358482125568321823.81:26.30.450.020.020.020.030.031.65Equatorial Guinea
Congo (Brazzaville)5.244354618995815893.61:27.40.450.020.020.020.020.020.3Congo (Brazzaville)
Gabon2.173778721275156090.91:109.90.720.010.010.010.010.010.63Gabon
Central African Republic5.496462029205916413.61:27.80.360.010.010.010.010.010.29Central African Republic
Chad15.69394228768389.11:11.00.890.080.080.080.080.080.13Chad
Angola31.1314838996452012.31:8.10.350.040.050.050.060.070.06Angola
Sao Tome and Principe0.287866157971.91:53.20.910.020.020.020.020.022.03Sao Tome and Principe
Middle Africa179.7751104135481012365442.81:36.10.720.020.020.020.020.020.15Middle 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