COVID-19 - Middle Africa - 20-06-03

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 17462 9.7 389 2.28% 3.18%
Active cases 11002 6.1 326 3.05% 3.01%
Deaths 413 0.2 3 0.73% 1.87%
Recovered 60473.4601.0%2.3%
Deaths per infected 2.37%
Recovered per infected34.63%
Active per infected 63.01%
Deaths per recovered 6.83%
Total Case Percentage

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 30d 18h 22d 2h
Time to reach a million cases 179d 16h129d 4h
Time to saturate the population>1yr 294d 20h

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 51
Active na 109 51
Deaths na 129 47
Recovered na 137 65
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!


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
absolute valuesPercentage growthrate 5dTime to doubleCases per 100.000% / ratio
Congo (Kinshasa)91.93134952928754924.293.250.873.8416d 11h80d 1h3.
Cameroon26.5466585270920036763.987.242.522.0617d 18h27d 20h24.810.20.813.85.41:18.40.56
Equatorial Guinea1.35813061094122000.
Congo (Brazzaville)5.244611412201791. 19h66d 4h11.
Gabon2.17329022081208012. 16h11d 12h133.695.80.936.92.51:40.00.28
Central African Republic5.496117311464236.134.2340.00.011d 15h2d 1h21.320.90.10.417.41:5.80.02
Chad15.693820164665901.56-6.670.314.8744d 17h225d 14h5.
Sao Tome and Principe0.248440412680. 9h242.0202.
Middle Africa179.77174621100241360473.183.011.872.322d 2h37d 11h9.

More Data by Country

Click top row to sort:±±±±±±±±±±±±±±±
CountryPop (mio)InfectedActiveDeathsRecoveredDeaths per RecoveredRecovered per
Deaths per infected ... days agoPossible
Total %
absolute values% / ratio0d5d7d10d14d
Congo (Kinshasa)91.931349529287549215.21: (Kinshasa)
Equatorial Guinea1.35813061094122006.01: Guinea
Congo (Brazzaville)5.2446114122017911.21: (Brazzaville)
Central African Republic5.4961173114642317.41: African Republic
Sao Tome and Principe0.2484404126817.61: Tome and Principe
Middle Africa179.77174621100241360476.81:14.60.350. 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