COVID-19 - WHO South-East Asia Region - 20-08-06

Data from JHU, ca. 9:00 CET

WHO South-East Asia Region is a Group with the following members:
Bangladesh - Bhutan - Burma - India - Indonesia - Korea, North - Maldives - Nepal - Pakistan - Sri Lanka - Thailand - Timor-Leste

Go to the data tables


absolutecases per 100.000 abs. development
1 day
rel. development
1 day
rel. development
5 days/average
Total infections 2710430 121.6 68575 2.6% 2.38%
Active cases 775961 34.8 11915 1.56% 0.71%
Deaths 56606 2.5 1020 1.83% 1.43%
Recovered 187786384.3556403.05%2.39%
Deaths per infected 2.09%
Recovered per infected69.28%
Active per infected 28.63%
Deaths per recovered 3.01%
Projection:
Total Case Percentage
0.69%

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 27d 1h 29d 10h
Time to reach a million cases
Time to saturate the population261d 22h 285d 2h

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 87 31
Active na 71 69
Deaths na 86 42
Recovered na 82 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!

Diagrams

Members of Group: WHO South-East Asia Region

Bangladesh - Bhutan - Burma - India - Indonesia - Korea, North - Maldives - Nepal - Pakistan - Sri Lanka - Thailand - Timor-Leste

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
Pakistan219.0172818631977060352560580.25-3.460.210.57272d 16h328d 20h128.79.02.8116.92.41:42.40.91
Indonesia266.912118753375875521756451.550.380.981.744d 22h71d 2h44.514.12.128.37.31:13.70.64
Thailand66.48433301245831480.111.170.00.06>1yr5.00.20.14.71.81:54.30.95
India1360.05420270746073844158513781052.970.961.733.0223d 15h40d 10h149.044.73.1101.33.01:33.10.68
Sri Lanka21.80328392871125410.17-4.140.00.8>1yr13.01.30.111.70.41:232.60.9
Bangladesh168.30424965110252133061438240.80.230.850.886d 13h82d 0h148.360.92.085.52.31:43.50.58
Maldives0.375468019361927253.467.352.290.6820d 8h30d 15h1248.7516.55.1727.10.71:142.90.58
Bhutan0.742108120961.16-1.5400.8960d 7h14.61.60.012.90.0na0.89
Nepal29.6121750629665153891.612.211.40.943d 12h49d 22h73.521.30.252.00.41:238.10.71
Burma68.673574363080.23-1.620.00.53307d 6h0.50.10.00.41.91:51.30.86
WHO South-East Asia Region2228.7827104307759615660618778632.380.711.432.3929d 10h48d 21h121.634.82.584.33.01:33.20.69

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
Pakistan219.0172818631977060352560582.41:42.40.910.020.020.020.020.020.74Pakistan
Indonesia266.912118753375875521756457.31:13.70.640.050.050.050.050.060.56Indonesia
Thailand66.48433301245831481.81:54.30.950.020.020.020.020.020.02Thailand
India1360.05420270746073844158513781053.01:33.10.680.020.020.020.030.030.83India
Sri Lanka21.80328392871125410.41:232.60.90.00.00.00.00.00.01Sri Lanka
Bangladesh168.30424965110252133061438242.31:43.50.580.010.010.010.010.020.53Bangladesh
Maldives0.375468019361927250.71:142.90.580.00.00.00.010.011.37Maldives
Bhutan0.742108120960.0na0.890.00.00.00.00.00.0Bhutan
Nepal29.6121750629665153890.41:238.10.710.00.00.00.00.00.06Nepal
Burma68.673574363081.91:51.30.860.020.020.020.020.020.0Burma
WHO South-East Asia Region2228.7827104307759615660618778633.01:33.20.690.020.020.020.030.030.69WHO South-East Asia Region

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