COVID-19 - Southern Asia - 20-10-09

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 8321943 434.5 81602 0.99% 1.0%
Active cases 1069787 55.9 -8141 -0.76% -0.56%
Deaths 149668 7.8 1171 0.79% 0.68%
Recovered 7102488370.8885721.26%1.02%
Deaths per infected 1.8%
Recovered per infected85.35%
Active per infected 12.86%
Deaths per recovered 2.11%
Projection:
Total Case Percentage
2.11%

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 70d 8h 69d 21h
Time to reach a million cases
Time to saturate the population>1yr >1yr

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 75 67
Active na 81 134
Deaths na 71 50
Recovered na 64 52
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
Iran83.29849237862901280984013790.862.170.680.4781d 1h101d 23h591.175.533.7481.97.01:14.30.82
Pakistan219.017318266864665583030620.23-1.740.120.25300d 10h>1yr145.33.93.0138.42.21:46.30.95
India1360.054697942388318510741659888221.05-0.890.731.1266d 6h95d 3h513.264.97.9440.31.81:55.90.86
Sri Lanka21.803452312141332966.1282.060.00.1211d 16h20.75.60.115.10.41:256.40.73
Afghanistan32.2263969351631472330580.180.240.110.13>1yr>1yr123.216.04.6102.64.51:22.50.83
Bangladesh168.3043758708048154772899120.39-0.210.420.47179d 16h167d 2h223.347.83.3172.31.91:52.90.77
Maldives0.3751080811203496540.52-0.190.00.48132d 23h2883.7298.89.12575.80.31:285.70.89
Bhutan0.7423062402820.53-4.0201.49130d 13h41.33.20.038.00.0na0.92
Nepal29.6110067627053600730233.013.851.982.1823d 8h35d 7h340.091.42.0246.60.81:122.00.73
Southern Asia1915.438321943106978714966871024881.0-0.560.681.0269d 21h102d 3h434.555.97.8370.82.11:47.40.85

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
Iran83.29849237862901280984013797.01:14.30.820.060.060.060.060.069.12Iran
Pakistan219.017318266864665583030622.21:46.30.950.020.020.020.020.020.81Pakistan
India1360.054697942388318510741659888221.81:55.90.860.020.020.020.020.022.13India
Sri Lanka21.803452312141332960.41:256.40.730.00.00.00.00.00.02Sri Lanka
Afghanistan32.2263969351631472330584.51:22.50.830.040.040.040.040.041.23Afghanistan
Bangladesh168.3043758708048154772899121.91:52.90.770.010.010.010.020.020.88Bangladesh
Maldives0.3751080811203496540.31:285.70.890.00.00.00.00.02.45Maldives
Bhutan0.7423062402820.0na0.920.00.00.00.00.00.0Bhutan
Nepal29.6110067627053600730230.81:122.00.730.010.010.010.010.010.55Nepal
Southern Asia1915.438321943106978714966871024882.11:47.40.850.020.020.020.020.022.11Southern 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