COVID-19 - Eastern Africa - 20-08-02

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 84813 20.8 2305 2.79% 3.14%
Active cases 39400 9.6 994 2.59% 2.9%
Deaths 1415 0.3 49 3.59% 3.2%
Recovered 4399810.812622.95%2.29%
Deaths per infected 1.67%
Recovered per infected51.88%
Active per infected 46.46%
Deaths per recovered 3.22%
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 25d 3h 22d 10h
Time to reach a million cases 89d 13h79d 19h
Time to saturate the population307d 17h 274d 5h

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 147 29
Active na 121 44
Deaths na 147 14
Recovered na 138 34
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
Rwanda12.3742062913511441.380.050.02.1950d 16h16.
Ethiopia98.665187061079531076014.274.593.562.016d 13h19d 19h19.
Kenya47.564220531320736984773.514.04.11.2720d 1h17d 5h46.427.80.817.84.31:23.00.38
Zambia17.3816347168417044934.963.393.125.714d 7h22d 13h36.
Djibouti1.0785161835950190.379.170.00.03189d 17h478.67.75.5465.41.21:84.70.97
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.
Eritrea3.52795402251.06-5.4103.5665d 22h8.
Mozambique30.0719461279136542.522.51.821.427d 21h38d 11h6.
Uganda40.31182133410450.82-1.7420.01.1285d 0h3d 19h2.
Burundi11.473959013040.893.530.00.278d 6h3.
Comoros0.853864973301.7827.060.00.1239d 7h45.45.80.838.82.11:47.20.85
Malawi18.144231218912319192.712.173.212.8525d 21h21d 23h23.312.10.710.66.41:15.60.45
South Sudan12.92242912084611751.060.860.00.065d 16h18.
Eastern Africa408.384813394001415439983. 10h22d 0h20.89.60.310.83.21:31.10.52

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 Sudan12.92242912084611753.91:25.60.480. Sudan
Eastern Africa408.384813394001415439983.21:31.10.520. 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