COVID-19 - Africa - 20-08-02

Data from JHU, ca. 9:00 CET

Africa is a Group with the following members:
Algeria - Angola - Benin - Botswana - Burkina Faso - Burundi - Cameroon - Central African Republic - Chad - Comoros - Congo (Brazzaville) - Congo (Kinshasa) - Cote d'Ivoire - Djibouti - Egypt - Equatorial Guinea - Eritrea - Eswatini - Ethiopia - Gabon - Gambia - Ghana - Guinea - Guinea-Bissau - Kenya - Lesotho - Liberia - Libya - Madagascar - Malawi - Mali - Mauritania - Mauritius - Mayotte - Morocco - Mozambique - Namibia - Niger - Nigeria - Reunion - Rwanda - Sao Tome and Principe - Senegal - Seychelles - Sierra Leone - Somalia - South Africa - South Sudan - Sudan - Tanzania - Togo - Tunisia - Uganda - Western Sahara - Zambia - Zimbabwe

Go to the data tables


absolutecases per 100.000 abs. development
1 day
rel. development
1 day
rel. development
5 days/average
Total infections 955212 74.4 12588 1.34% 1.86%
Active cases 324758 25.3 3255 1.01% -0.53%
Deaths 20283 1.6 332 1.66% 1.56%
Recovered 61017147.590011.5%2.87%
Deaths per infected 2.12%
Recovered per infected63.88%
Active per infected 34.0%
Deaths per recovered 3.32%
Projection:
Total Case Percentage
0.43%

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 52d 6h 37d 17h
Time to reach a million cases 3d 10h2d 11h
Time to saturate the population>1yr >1yr

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 98 54
Active na 84 136
Deaths na 100 42
Recovered na 95 27
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: Africa

Algeria - Angola - Benin - Botswana - Burkina Faso - Burundi - Cameroon - Central African Republic - Chad - Comoros - Congo (Brazzaville) - Congo (Kinshasa) - Cote d'Ivoire - Djibouti - Egypt - Equatorial Guinea - Eritrea - Eswatini - Ethiopia - Gabon - Gambia - Ghana - Guinea - Guinea-Bissau - Kenya - Lesotho - Liberia - Libya - Madagascar - Malawi - Mali - Mauritania - Mauritius - Mayotte - Morocco - Mozambique - Namibia - Niger - Nigeria - Reunion - Rwanda - Sao Tome and Principe - Senegal - Seychelles - Sierra Leone - Somalia - South Africa - South Sudan - Sudan - Tanzania - Togo - Tunisia - Uganda - Western Sahara - Zambia - Zimbabwe

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
Egypt100.1594483471634865424550.33-1.540.62.76211d 7h115d 3h94.347.14.942.411.51:8.70.45
South Africa58.77551148515589283663472272.16-1.522.373.6532d 8h29d 12h870.2265.214.2590.82.41:41.50.68
Algeria43.03146588151231214191.921.270.821.7836d 8h84d 11h73.220.52.949.85.81:17.40.68
Morocco35.845255376720382184353.6411.252.361.0419d 9h29d 17h71.218.71.151.42.11:48.30.72
Tunisia11.72215612895112211.242.610.40.8356d 5h173d 15h13.32.50.410.44.21:23.90.78
Burkina Faso20.871143145539450.694.980.00.19101d 5h5.50.70.34.55.61:17.80.83
Senegal16.20910344329720968381.081.531.090.6964d 15h63d 19h63.820.31.342.23.11:32.70.66
Congo (Kinshasa)91.9319115158121573190.54-7.240.673.52128d 16h104d 0h9.91.70.28.02.91:34.00.8
Cameroon26.546172551544391153200.09-6.270.01.07stable65.05.81.557.72.51:39.20.89
Nigeria206.144384122645888203080.960.350.341.3872d 16h202d 1h21.311.00.49.94.41:22.90.46
Ghana30.281370143467182333651.49-0.811.631.7646d 18h42d 18h122.211.40.6110.20.61:181.80.9
Cote d'Ivoire23.74161824279102118010.59-3.40.812.22117d 17h86d 8h68.218.00.449.70.91:116.30.73
Rwanda12.3742062913511441.380.050.02.1950d 16h16.77.40.09.20.41:227.30.55
Ethiopia98.665187061079531076014.274.593.562.016d 13h19d 19h19.010.90.37.74.11:24.50.41
Kenya47.564220531320736984773.514.04.11.2720d 1h17d 5h46.427.80.817.84.31:23.00.38
Mauritius1.2663442103320.00.00.00.027.20.20.826.23.01:33.20.97
Tanzania55.891509305211830.00.00.00.00.90.50.00.311.51:8.70.36
Equatorial Guinea1.3584821255683218211.43.4712.5531.836d 10h5d 20h354.9188.26.1160.63.81:26.30.45
Congo (Brazzaville)5.24432002317548290.00.00.00.061.044.21.015.86.51:15.40.26
Namibia2.45922942096111873.692.556.7212.3919d 3h10d 15h93.385.20.47.65.91:17.00.08
Liberia4.4751207457776730.51-0.790.830.83137d 6h84d 6h27.010.21.715.011.41:8.70.56
Benin11.73318057333610360.40.970.570.0175d 14h121d 15h15.46.20.38.83.51:28.80.57
Sudan42.36111738484975261370.420.330.740.45164d 23h93d 9h27.711.41.814.512.21:8.20.52
Zambia17.3816347168417044934.963.393.125.714d 7h22d 13h36.59.71.025.83.81:26.50.71
Mauritania4.0776323105115751150.24-4.430.131.5294d 5h>1yr155.125.83.9125.53.11:32.60.81
Gabon2.173753122585052230.94-1.660.412.2574d 1h170d 4h346.6103.92.3240.41.01:104.20.69
Somalia15.893322015299315980.050.00.00.0stable20.39.60.610.15.81:17.20.5
Togo7.538961282196601.431.971.111.1348d 18h62d 17h12.73.70.38.82.91:34.70.69
Central African Republic5.496461429205916350.07-0.50.01.14stable84.053.11.129.73.61:27.70.35
Niger22.3151147466910320.261.640.00.02262d 15h5.10.20.34.66.71:14.90.9
Guinea12.21873177914664800.530.980.00.46130d 20h59.96.50.453.00.71:140.80.89
Chad15.69393648758130.223.70.00.07321d 13h6.00.30.55.29.21:10.80.87
Djibouti1.0785161835950190.379.170.00.03189d 17h478.67.75.5465.41.21:84.70.97
Eswatini1.093277515184312142.941.642.013.4923d 22h34d 18h253.8138.93.9111.13.51:28.20.44
Gambia2.3484984219689.4411.72.50.617d 16h28d 1h21.217.90.42.913.21:7.60.14
Madagascar25.6811528297011484442.69-2.012.884.2326d 3h24d 9h44.911.60.432.91.41:74.10.73
Zimbabwe15.16392128357010167.024.0312.3912.0910d 5h5d 22h25.918.70.56.76.91:14.50.26
Angola31.131199683554613.73-0.982.8512.1718d 22h24d 15h3.92.20.21.511.91:8.40.38
Eritrea3.52795402251.06-5.4103.5665d 22h8.01.50.06.40.0na0.81
Mozambique30.0719461279136542.522.51.821.427d 21h38d 11h6.54.30.02.22.01:50.30.34
Uganda40.31182133410450.82-1.7420.01.1285d 0h3d 19h2.90.30.02.60.41:263.20.88
Libya6.7538373131836234.964.843.811.3514d 7h18d 12h56.846.41.29.213.31:7.50.16
Guinea-Bissau1.8619811151278030.280.460.770.0251d 3h90d 10h106.561.91.543.23.41:29.80.41
Mali18.43254147412419430.17-0.120.00.19>1yr13.82.60.710.56.41:15.70.76
Botswana2.258047392631.761.930.00.039d 17h35.732.80.12.83.21:31.50.08
Burundi11.473959013040.893.530.00.278d 6h3.40.80.02.70.31:303.00.77
Comoros0.853864973301.7827.060.00.1239d 7h45.45.80.838.82.11:47.20.85
Lesotho2.11718526191737.487.443.216.219d 14h21d 23h34.024.90.98.211.01:9.10.24
Malawi18.144231218912319192.712.173.212.8525d 21h21d 23h23.312.10.710.66.41:15.60.45
Sao Tome and Principe0.287472157870.16-3.851.430.6>1yr48d 20h437.036.07.5393.51.91:52.40.9
Africa1284.47955212324758202836101711.86-0.531.562.8737d 17h44d 20h74.425.31.647.53.31:30.10.64
South Sudan12.92242912084611750.010.010.00.065d 16h18.89.30.49.10.01:2554.30.0
Sierra Leone7.0818434016713750.010.010.00.0110d 3h229d 2h26.05.70.919.40.01:2052.20.01

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
Egypt100.15944834716348654245511.51:8.70.450.050.050.050.050.061.31Egypt
South Africa58.77551148515589283663472272.41:41.50.680.020.020.020.020.023.85South Africa
Algeria43.03146588151231214195.81:17.40.680.040.040.040.050.050.77Algeria
Morocco35.845255376720382184352.11:48.30.720.010.020.020.020.020.29Morocco
Tunisia11.72215612895112214.21:23.90.780.030.030.040.040.040.12Tunisia
Burkina Faso20.871143145539455.61:17.80.830.050.050.050.050.050.07Burkina Faso
Senegal16.20910344329720968383.11:32.70.660.020.020.020.020.020.35Senegal
Congo (Kinshasa)91.9319115158121573192.91:34.00.80.020.020.020.020.030.06Congo (Kinshasa)
Cameroon26.546172551544391153202.51:39.20.890.020.020.020.020.020.4Cameroon
Nigeria206.144384122645888203084.41:22.90.460.020.020.020.020.020.12Nigeria
Ghana30.281370143467182333650.61:181.80.90.00.010.010.010.010.16Ghana
Cote d'Ivoire23.74161824279102118010.91:116.30.730.010.010.010.010.010.12Cote d'Ivoire
Rwanda12.3742062913511440.41:227.30.550.00.00.00.00.00.01Rwanda
Ethiopia98.665187061079531076014.11:24.50.410.020.020.020.020.030.08Ethiopia
Kenya47.564220531320736984774.31:23.00.380.020.020.020.020.030.21Kenya
Mauritius1.2663442103323.01:33.20.970.030.030.030.030.030.21Mauritius
Tanzania55.8915093052118311.51:8.70.360.040.040.040.040.040.01Tanzania
Equatorial Guinea1.358482125568321823.81:26.30.450.020.030.030.030.031.65Equatorial Guinea
Congo (Brazzaville)5.24432002317548296.51:15.40.260.020.020.020.020.020.28Congo (Brazzaville)
Namibia2.45922942096111875.91:17.00.080.00.010.010.010.010.12Namibia
Liberia4.47512074577767311.41:8.70.560.060.070.070.070.070.47Liberia
Benin11.73318057333610363.51:28.80.570.020.020.020.020.020.08Benin
Sudan42.361117384849752613712.21:8.20.520.060.070.070.070.070.48Sudan
Zambia17.3816347168417044933.81:26.50.710.030.030.040.040.050.26Zambia
Mauritania4.0776323105115751153.11:32.60.810.020.030.030.030.031.04Mauritania
Gabon2.173753122585052231.01:104.20.690.010.010.010.010.010.62Gabon
Somalia15.893322015299315985.81:17.20.50.030.030.030.030.030.16Somalia
Togo7.538961282196602.91:34.70.690.020.020.020.020.020.07Togo
Central African Republic5.496461429205916353.61:27.70.350.010.010.010.010.010.29Central African Republic
Niger22.3151147466910326.71:14.90.90.060.060.060.060.060.08Niger
Guinea12.21873177914664800.71:140.80.890.010.010.010.010.010.1Guinea
Chad15.69393648758139.21:10.80.870.080.080.080.080.080.13Chad
Djibouti1.0785161835950191.21:84.70.970.010.010.010.010.011.48Djibouti
Eswatini1.093277515184312143.51:28.20.440.020.020.020.020.021.06Eswatini
Gambia2.34849842196813.21:7.60.140.020.030.030.040.080.1Gambia
Madagascar25.6811528297011484441.41:74.10.730.010.010.010.010.020.12Madagascar
Zimbabwe15.16392128357010166.91:14.50.260.020.020.030.030.040.12Zimbabwe
Angola31.1311996835546111.91:8.40.380.050.050.060.060.070.05Angola
Eritrea3.52795402250.0na0.810.00.00.00.00.00.0Eritrea
Mozambique30.0719461279136542.01:50.30.340.010.010.010.010.010.01Mozambique
Uganda40.31182133410450.41:263.20.880.00.00.00.00.00.0Uganda
Libya6.75383731318362313.31:7.50.160.020.030.030.030.040.33Libya
Guinea-Bissau1.8619811151278033.41:29.80.410.010.010.010.010.010.39Guinea-Bissau
Mali18.43254147412419436.41:15.70.760.050.050.050.050.050.18Mali
Botswana2.258047392633.21:31.50.080.00.00.00.00.00.02Botswana
Burundi11.473959013040.31:303.00.770.00.00.00.00.00.0Burundi
Comoros0.853864973302.11:47.20.850.020.020.020.020.020.22Comoros
Lesotho2.117185261917311.01:9.10.240.030.030.040.050.050.24Lesotho
Malawi18.144231218912319196.41:15.60.450.030.030.030.040.040.18Malawi
Sao Tome and Principe0.287472157871.91:52.40.90.020.020.020.020.022.03Sao Tome and Principe
Africa1284.47955212324758202836101713.31:30.10.640.020.020.020.030.030.43Africa
South Sudan12.92242912084611750.01:2554.30.00.00.020.020.020.020.1South Sudan
Sierra Leone7.0818434016713750.01:2052.20.010.00.040.040.040.040.26Sierra Leone

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