COVID-19 - Eastern Africa - 20-08-06

Data from JHU, ca. 9:00 CET

Eastern Africa is a Group with the following members:
Burundi - Comoros - Djibouti - Eritrea - Ethiopia - Kenya - Madagascar - Malawi - Mauritius - Mayotte - Mozambique - Reunion - Rwanda - Seychelles - Somalia - South Sudan - Tanzania - Uganda - 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 92349 22.6 1815 2.0% 2.28%
Active cases 39337 9.6 229 0.59% 0.37%
Deaths 1581 0.4 51 3.33% 2.3%
Recovered 5143112.615353.08%3.16%
Deaths per infected 1.71%
Recovered per infected55.69%
Active per infected 42.6%
Deaths per recovered 3.07%
Projection:
Total Case Percentage
0.1%

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 34d 22h 30d 18h
Time to reach a million cases 120d 0h105d 16h
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 146 33
Active na 117 80
Deaths na 145 27
Recovered na 140 22
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: Eastern Africa

Burundi - Comoros - Djibouti - Eritrea - Ethiopia - Kenya - Madagascar - Malawi - Mauritius - Mayotte - Mozambique - Reunion - Rwanda - Seychelles - Somalia - South Sudan - Tanzania - Uganda - 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
Rwanda12.3742111848512580.67-1.230.02.04104d 2h17.16.90.010.20.41:250.00.6
Ethiopia98.665209001150836590273.041.594.683.6523d 4h15d 3h21.211.70.49.14.01:24.80.43
Kenya47.5642441113568399104442.71.521.453.3925d 23h48d 5h51.328.50.822.03.81:26.20.43
Mauritius1.2663440103340.000.00.1227.20.00.826.43.01:33.40.97
Tanzania55.891509305211830.00.00.00.00.90.50.00.311.51:8.70.36
Zambia17.3817164117919957862.84-8.991.36.624d 17h53d 11h41.26.81.133.33.41:29.10.81
Somalia15.893322714069317280.09-1.970.02.09stable20.38.80.610.95.41:18.60.54
Djibouti1.07853302145950570.9566.820.340.2373d 3h201d 8h494.319.85.5468.91.21:85.50.95
Madagascar25.68125262244134101482.13-5.493.513.8832d 20h20d 2h48.88.70.539.51.31:75.80.81
Zimbabwe15.16433929918412643.492.473.44.3320d 4h20d 17h28.619.70.68.36.71:15.00.29
Eritrea3.52825702250.221.1100.0322d 15h8.11.60.06.40.0na0.8
Mozambique30.0721201310157952.140.594.633.9232d 17h15d 7h7.14.40.02.61.91:52.90.38
Uganda40.31223116511020.79-3.225.01.0888d 10h14d 4h3.00.30.02.70.51:222.20.9
Burundi11.474009513040.250.00.00.0274d 3h3.50.80.02.70.31:303.00.76
Comoros0.853964973400.52-3.270.00.61134d 16h46.65.80.840.02.11:48.50.86
Malawi18.144491221713721371.420.562.561.6749d 6h27d 9h24.812.20.811.86.41:15.60.48
South Sudan12.92245012284711750.831.480.430.084d 3h159d 18h19.09.50.49.14.01:25.00.48
Eastern Africa408.392349393371581514312.280.372.33.1630d 18h30d 10h22.69.60.412.63.11:32.60.56

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
Rwanda12.3742111848512580.41:250.00.60.00.00.00.00.00.01Rwanda
Ethiopia98.665209001150836590274.01:24.80.430.020.020.020.020.030.1Ethiopia
Kenya47.5642441113568399104443.81:26.20.430.020.020.020.020.020.23Kenya
Mauritius1.2663440103343.01:33.40.970.030.030.030.030.030.21Mauritius
Tanzania55.8915093052118311.51:8.70.360.040.040.040.040.040.01Tanzania
Zambia17.3817164117919957863.41:29.10.810.030.030.030.040.050.31Zambia
Somalia15.893322714069317285.41:18.60.540.030.030.030.030.030.16Somalia
Djibouti1.07853302145950571.21:85.50.950.010.010.010.010.011.48Djibouti
Madagascar25.68125262244134101481.31:75.80.810.010.010.010.010.020.14Madagascar
Zimbabwe15.16433929918412646.71:15.00.290.020.020.020.030.040.15Zimbabwe
Eritrea3.52825702250.0na0.80.00.00.00.00.00.0Eritrea
Mozambique30.0721201310157951.91:52.90.380.010.010.010.010.010.01Mozambique
Uganda40.31223116511020.51:222.20.90.00.00.00.00.00.0Uganda
Burundi11.474009513040.31:303.00.760.00.00.00.00.00.0Burundi
Comoros0.853964973402.11:48.50.860.020.020.020.020.020.22Comoros
Malawi18.144491221713721376.41:15.60.480.030.030.030.040.040.2Malawi
South Sudan12.92245012284711754.01:25.00.480.020.020.020.020.020.1South Sudan
Eastern Africa408.392349393371581514313.11:32.60.560.020.020.020.020.020.1Eastern 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