COVID-19 - Southern Asia - 20-11-27

Data from JHU, ca. 9:00 CET

Southern Asia is a Group with the following members:
Afghanistan - Bangladesh - Bhutan - India - Iran - Maldives - Nepal - Pakistan - Sri Lanka

Go to the data tables


absolutecases per 100.000 abs. development
1 day
rel. development
1 day
rel. development
5 days/average
Total infections 11435584 597.0 63040 0.55% 0.57%
Active cases 849135 44.3 9404 1.12% 0.96%
Deaths 201109 10.5 990 0.49% 0.44%
Recovered 10385340542.2526460.51%0.42%
Deaths per infected 1.76%
Recovered per infected90.82%
Active per infected 7.43%
Deaths per recovered 1.94%
Projection:
Total Case Percentage
2.84%

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 125d 9h 122d 12h
Time to reach a million cases
Time to saturate the populationstable 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: 192Population na
Total casesCases per 100.000Average grow rate (5 days)
Infected na 91 102
Active na 96 70
Deaths na 81 77
Recovered na 76 90
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: Southern Asia

Afghanistan - Bangladesh - Bhutan - India - Iran - Maldives - Nepal - Pakistan - Sri Lanka

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
Iran83.298922397235237470956400651.542.080.830.9745d 5h83d 22h1107.3282.456.5768.47.41:13.60.69
Pakistan219.0173923564686179423375530.813.510.520.386d 9h134d 7h179.121.43.6154.12.41:42.60.86
India1360.054935110945494013620087599690.460.540.290.36151d 16h236d 2h687.633.510.0644.11.61:64.50.94
Sri Lanka21.803225016168107162262.210.342.632.3831d 16h26d 17h103.228.30.574.40.71:151.50.72
Afghanistan32.2264583978041740362950.51.810.590.17138d 10h118d 13h142.224.25.4112.64.81:20.90.79
Bangladesh168.3044587117849165443736760.5-0.020.420.49138d 1h164d 10h272.546.63.9222.01.81:57.10.81
Maldives0.37512933113846117490.513.310.00.2136d 0h3450.6303.612.33134.70.41:256.40.91
Bhutan0.7423952303720.67-0.4600.44103d 6h53.33.10.050.20.0na0.94
Nepal29.612293431847314352094350.81-3.351.341.0386d 5h51d 22h774.662.44.8707.30.71:144.90.91
Southern Asia1915.4311435584849135201109103853400.570.960.440.42122d 12h157d 11h597.044.310.5542.21.91:51.50.91

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
Iran83.298922397235237470956400657.41:13.60.690.050.050.060.060.0615.28Iran
Pakistan219.0173923564686179423375532.41:42.60.860.020.020.020.020.020.98Pakistan
India1360.054935110945494013620087599691.61:64.50.940.010.010.010.020.022.71India
Sri Lanka21.803225016168107162260.71:151.50.720.00.010.010.010.010.13Sri Lanka
Afghanistan32.2264583978041740362954.81:20.90.790.040.040.040.040.041.46Afghanistan
Bangladesh168.3044587117849165443736761.81:57.10.810.010.010.010.010.021.05Bangladesh
Maldives0.37512933113846117490.41:256.40.910.00.00.00.00.03.32Maldives
Bhutan0.7423952303720.0na0.940.00.00.00.00.00.0Bhutan
Nepal29.612293431847314352094350.71:144.90.910.010.010.010.010.011.31Nepal
Southern Asia1915.4311435584849135201109103853401.91:51.50.910.020.020.020.020.022.84Southern Asia

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