COVID-19 - Eastern Africa - 20-06-03

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 15674 3.8 608 4.04% 4.52%
Active cases 10298 2.5 426 4.32% 3.99%
Deaths 265 0.1 7 2.71% 2.51%
Recovered 51111.31753.55%3.27%
Deaths per infected 1.69%
Recovered per infected32.61%
Active per infected 65.7%
Deaths per recovered 5.18%
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 17d 12h 15d 16h
Time to reach a million cases 105d 1h93d 22h
Time to saturate the population257d 0h 229d 19h

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 156 37
Active na 129 37
Deaths na 146 39
Recovered na 152 42
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: 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
absolute valuesPercentage growthrate 5dTime to doubleCases per 100.000% / ratio
Rwanda12.37439712422712.260.9301.7330d 22h3.
Ethiopia98.66514861223172468.967.6612.653.278d 1h5d 19h1.
Kenya47.56422161589745534.914.162.782.6614d 10h25d 6h4.
Zambia17.381108917079120.61-7.450.03.41114d 19h6.
Somalia15.89321461661794063.262.681.93.1321d 14h36d 17h13.510.50.52.619.51:5.10.19
Djibouti1.078393522732616366.215.574.655.4711d 12h15d 5h364.9210.82.4151.71.61:62.90.42
Madagascar25.6890870761955.444.424.02.4613d 2h17d 16h3.
Zimbabwe15.162221894298.478.470.00.718d 12h1.
Mozambique30.0731620521096.437.690.03.1811d 2h1.
Uganda40.35074250829.3610.2302.787d 18h1.
Comoros0.851321032279.2711.980.02.447d 19h15.512.
Malawi18.143693144516.386.840.00.011d 4h2.
South Sudan12.929949781060.
Eastern Africa408.3156741029826551114.523.992.513.2715d 16h27d 21h3.

More Data by Country

Click top row to sort:±±±±±±±±±±±±±±±
CountryPop (mio)InfectedActiveDeathsRecoveredDeaths per RecoveredRecovered per
Deaths per infected ... days agoPossible
Total %
absolute values% / ratio0d5d7d10d14d
South Sudan12.92994978106166.71.7: Sudan
Eastern Africa408.3156741029826551115.21:19.30.330. 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