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
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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 | |
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Time to double cases | 158d 21h | 165d 14h |
Time to reach a million cases | >1yr | >1yr |
Time to saturate the population | stable | 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: | 192 | Population | na |
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Total cases | Cases per 100.000 | Average 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! |
Click top row to sort: | ± | ± | ± | ± | ± | ± | ± | ± | ± | ± | ± | ± | ± | ± | ± | ± | ± | ± |
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Country | Pop (mio) | Infected | Active | Deaths | Recovered | Infected | Active | Deaths | Recovered | Infected | Deaths | Infected | Active | Deaths | Recovered | Deaths per Recovered | Recovered per infected | |
absolute values | Percentage growthrate 5d | Time to double | Cases per 100.000 | % / ratio | ||||||||||||||
Congo (Kinshasa) | 91.931 | 12470 | 642 | 333 | 11495 | 0.47 | 3.14 | 0.36 | 0.34 | 147d 3h | 190d 9h | 13.6 | 0.7 | 0.4 | 12.5 | 2.9 | 1:34.5 | 0.92 |
Cameroon | 26.546 | 24117 | 1503 | 437 | 22177 | 0.5 | 9.64 | 0.09 | 0.0 | 139d 21h | stable | 90.9 | 5.7 | 1.6 | 83.5 | 2.0 | 1:50.8 | 0.92 |
Equatorial Guinea | 1.358 | 5146 | 56 | 85 | 5005 | 0.06 | -2.74 | 0.0 | 0.12 | stable | 378.9 | 4.1 | 6.3 | 368.5 | 1.7 | 1:58.8 | 0.97 | |
Congo (Brazzaville) | 5.244 | 5774 | 692 | 94 | 4988 | 0.5 | -13.33 | 0.0 | 5.67 | 137d 19h | 110.1 | 13.2 | 1.8 | 95.1 | 1.9 | 1:53.2 | 0.86 | |
Gabon | 2.173 | 9191 | 95 | 59 | 9037 | 0.13 | 0.47 | 0.0 | 0.09 | >1yr | 423.0 | 4.4 | 2.7 | 416.0 | 0.7 | 1:153.8 | 0.98 | |
Central African Republic | 5.496 | 4913 | 2926 | 63 | 1924 | 0.01 | 0.01 | 0.0 | 0.0 | stable | 89.4 | 53.2 | 1.1 | 35.0 | 3.3 | 1:30.6 | 0.39 | |
Chad | 15.693 | 1663 | 63 | 101 | 1499 | 0.25 | -1.63 | 0.0 | 0.37 | 272d 14h | 10.6 | 0.4 | 0.6 | 9.6 | 6.7 | 1:14.8 | 0.9 | |
Angola | 31.13 | 15008 | 6969 | 342 | 7697 | 0.7 | 0.45 | 0.24 | 0.73 | 99d 5h | 293d 9h | 48.2 | 22.4 | 1.1 | 24.7 | 4.4 | 1:22.5 | 0.51 |
Sao Tome and Principe | 0.2 | 985 | 40 | 17 | 928 | 0.12 | 0.53 | 0.0 | 0.11 | >1yr | 492.5 | 20.0 | 8.5 | 464.0 | 1.8 | 1:54.6 | 0.94 | |
Middle Africa | 179.77 | 79267 | 12986 | 1531 | 64750 | 0.42 | -0.57 | 0.16 | 0.53 | 165d 14h | >1yr | 44.1 | 7.2 | 0.9 | 36.0 | 2.4 | 1:42.4 | 0.82 |
Click top row to sort: | ± | ± | ± | ± | ± | ± | ± | ± | ± | ± | ± | ± | ± | ± | ± |
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Country | Pop (mio) | Infected | Active | Deaths | Recovered | Deaths per Recovered | Recovered per infected | Deaths per infected ... days ago | Possible Total % | Country | |||||
absolute values | % / ratio | 0d | 5d | 7d | 10d | 14d | |||||||||
Congo (Kinshasa) | 91.931 | 12470 | 642 | 333 | 11495 | 2.9 | 1:34.5 | 0.92 | 0.03 | 0.03 | 0.03 | 0.03 | 0.03 | 0.1 | Congo (Kinshasa) |
Cameroon | 26.546 | 24117 | 1503 | 437 | 22177 | 2.0 | 1:50.8 | 0.92 | 0.02 | 0.02 | 0.02 | 0.02 | 0.02 | 0.44 | Cameroon |
Equatorial Guinea | 1.358 | 5146 | 56 | 85 | 5005 | 1.7 | 1:58.8 | 0.97 | 0.02 | 0.02 | 0.02 | 0.02 | 0.02 | 1.69 | Equatorial Guinea |
Congo (Brazzaville) | 5.244 | 5774 | 692 | 94 | 4988 | 1.9 | 1:53.2 | 0.86 | 0.02 | 0.02 | 0.02 | 0.02 | 0.02 | 0.48 | Congo (Brazzaville) |
Gabon | 2.173 | 9191 | 95 | 59 | 9037 | 0.7 | 1:153.8 | 0.98 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.73 | Gabon |
Central African Republic | 5.496 | 4913 | 2926 | 63 | 1924 | 3.3 | 1:30.6 | 0.39 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.31 | Central African Republic |
Chad | 15.693 | 1663 | 63 | 101 | 1499 | 6.7 | 1:14.8 | 0.9 | 0.06 | 0.06 | 0.06 | 0.06 | 0.06 | 0.17 | Chad |
Angola | 31.13 | 15008 | 6969 | 342 | 7697 | 4.4 | 1:22.5 | 0.51 | 0.02 | 0.02 | 0.02 | 0.02 | 0.03 | 0.3 | Angola |
Sao Tome and Principe | 0.2 | 985 | 40 | 17 | 928 | 1.8 | 1:54.6 | 0.94 | 0.02 | 0.02 | 0.02 | 0.02 | 0.02 | 2.3 | Sao Tome and Principe |
Middle Africa | 179.77 | 79267 | 12986 | 1531 | 64750 | 2.4 | 1:42.4 | 0.82 | 0.02 | 0.02 | 0.02 | 0.02 | 0.02 | 0.23 | Middle Africa |
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 |