COVID-19 - WHO South-East Asia Region - 20-08-02

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 2466710 110.7 57245 2.38% 3.11%
Active cases 750152 33.7 12542 1.7% 2.08%
Deaths 52651 2.4 863 1.67% 1.83%
Recovered 166390774.7438402.71%2.92%
Deaths per infected 2.13%
Recovered per infected67.45%
Active per infected 30.41%
Deaths per recovered 3.16%
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 29d 12h 22d 15h
Time to reach a million cases
Time to saturate the population289d 20h 222d 10h

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 88 31
Active na 71 57
Deaths na 87 36
Recovered na 82 26
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: 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
absolute valuesPercentage growthrate 5dTime to doubleCases per 100.000% / ratio
Pakistan219.0172796992514659762485770.32-1.310.290.39214d 19h237d 20h127.711.52.7113.52.41:41.70.89
Indonesia266.912111455372445236689751.780.121.172.3539d 4h59d 14h41.814.
India1360.05418036955793573813511862034.022.732.273.8217d 13h30d 19h132.642.62.887.23.21:31.20.66
Sri Lanka21.80328232981125140.09-
Bangladesh168.30424074610075331541368390.990.340.871.3670d 5h80d 5h143.059.91.981.32.31:43.50.57
Maldives0.375416415031826433.537.132.580.5220d 0h27d 4h1111.0401.04.8705.20.71:147.10.63
Bhutan0.742102130890.60.000.69115d 11h13.
Nepal29.6120332567257146031.31.532.760.8853d 14h25d 10h68.719.
WHO South-East Asia Region2228.7824667107501525265116639073.112.081.832.9222d 15h38d 5h110.733.72.474.73.21:31.60.67

More Data by Country

Click top row to sort:±±±±±±±±±±±±±±±
CountryPop (mio)InfectedActiveDeathsRecoveredDeaths per RecoveredRecovered per
Deaths per infected ... days agoPossible
Total %
absolute values% / ratio0d5d7d10d14d
Sri Lanka21.80328232981125140.41:227.30.890. Lanka
WHO South-East Asia Region2228.7824667107501525265116639073.21:31.60.670. 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