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


absolutecases 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 6475036.01040.16%0.53%
Deaths per infected 1.93%
Recovered per infected81.69%
Active per infected 16.38%
Deaths per recovered 2.36%
Projection:
Total Case Percentage
0.23%

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 158d 21h 165d 14h
Time to reach a million cases >1yr>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: 192Population na
Total casesCases per 100.000Average 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:±±±±±±±±±±±±±±±±±±
CountryPop (mio)InfectedActiveDeathsRecoveredInfectedActiveDeathsRecoveredInfectedDeathsInfectedActiveDeathsRecoveredDeaths per RecoveredRecovered per
infected
absolute valuesPercentage growthrate 5dTime to doubleCases per 100.000% / ratio
Congo (Kinshasa)91.93112470642333114950.473.140.360.34147d 3h190d 9h13.60.70.412.52.91:34.50.92
Cameroon26.546241171503437221770.59.640.090.0139d 21hstable90.95.71.683.52.01:50.80.92
Equatorial Guinea1.3585146568550050.06-2.740.00.12stable378.94.16.3368.51.71:58.80.97
Congo (Brazzaville)5.24457746929449880.5-13.330.05.67137d 19h110.113.21.895.11.91:53.20.86
Gabon2.1739191955990370.130.470.00.09>1yr423.04.42.7416.00.71:153.80.98
Central African Republic5.496491329266319240.010.010.00.0stable89.453.21.135.03.31:30.60.39
Chad15.69316636310114990.25-1.630.00.37272d 14h10.60.40.69.66.71:14.80.9
Angola31.1315008696934276970.70.450.240.7399d 5h293d 9h48.222.41.124.74.41:22.50.51
Sao Tome and Principe0.298540179280.120.530.00.11>1yr492.520.08.5464.01.81:54.60.94
Middle Africa179.7779267129861531647500.42-0.570.160.53165d 14h>1yr44.17.20.936.02.41:42.40.82

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)91.93112470642333114952.91:34.50.920.030.030.030.030.030.1Congo (Kinshasa)
Cameroon26.546241171503437221772.01:50.80.920.020.020.020.020.020.44Cameroon
Equatorial Guinea1.3585146568550051.71:58.80.970.020.020.020.020.021.69Equatorial Guinea
Congo (Brazzaville)5.24457746929449881.91:53.20.860.020.020.020.020.020.48Congo (Brazzaville)
Gabon2.1739191955990370.71:153.80.980.010.010.010.010.010.73Gabon
Central African Republic5.496491329266319243.31:30.60.390.010.010.010.010.010.31Central African Republic
Chad15.69316636310114996.71:14.80.90.060.060.060.060.060.17Chad
Angola31.1315008696934276974.41:22.50.510.020.020.020.020.030.3Angola
Sao Tome and Principe0.298540179281.81:54.60.940.020.020.020.020.022.3Sao Tome and Principe
Middle Africa179.7779267129861531647502.41:42.40.820.020.020.020.020.020.23Middle 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