COVID-19 - Most Populous - 20-11-27

Data from JHU, ca. 9:00 CET

Most Populous is a Group with the following members:
Bangladesh - Brazil - China - Ethiopia - India - Indonesia - Japan - Mexico - Nigeria - Pakistan - Philippines - Russia - US

Go to the data tables

absolutecases per 100.000 abs. development
1 day
rel. development
1 day
rel. development
5 days/average
Total infections 34164153 716.3 324709 0.96% 0.87%
Active cases 9738626 204.2 142829 1.49% 0.77%
Deaths 764338 16.0 3185 0.42% 0.43%
Recovered 23661189496.11786950.76%0.65%
Deaths per infected 2.24%
Recovered per infected69.26%
Active per infected 28.51%
Deaths per recovered 3.23%
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 72d 13h 79d 15h
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: 192Population na
Total casesCases per 100.000Average grow rate (5 days)
Infected na 86 81
Active na 62 77
Deaths na 71 77
Recovered na 81 73
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: Most Populous

Bangladesh - Brazil - China - Ethiopia - India - Indonesia - Japan - Mexico - Nigeria - Pakistan - Philippines - Russia - US

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
US329.48813088821787651726485849474461.340.750.511.4852d 2h136d 17h3972.52390.580.41501.65.31:18.70.38
Japan126.011427782304120281177091.421.130.541.0649d 0h128d 15h113.318.31.693.41.71:58.10.82
Brazil211.284623835048494017197455814360.541.410.270.36127d 17h259d 2h2952.6229.581.42641.73.11:32.50.89
Pakistan219.0173923564686179423375530.813.510.520.386d 9h134d 7h179.121.43.6154.12.41:42.60.86
Indonesia266.91252258168604165214374560.980.980.580.7370d 22h119d 6h195.825.76.2163.93.81:26.50.84
Philippines108.4344259183004782553876160.343.550.290.04206d 3h238d 2h392.827.77.6357.52.11:46.90.91
Russia146.74521966914608983817516976181.180.321.011.159d 5h68d 18h1496.9314.126.01156.82.21:44.40.77
India1360.054935110945494013620087599690.460.540.290.36151d 16h236d 2h687.633.510.0644.11.61:64.50.94
Mexico126.57810785941707711042428035810. 23h138d 21h852.1134.982.4634.913.01:7.70.74
Bangladesh168.3044587117849165443736760.5-0.020.420.49138d 1h164d 10h272.546.63.9222.01.81:57.10.81
Nigeria206.146722033631171626860.250.530.030.16276d 13hstable32.61.60.630.41.91:53.50.93
Ethiopia98.665108438392461686675060. 21h229d 20h109.939.81.768.42.51:40.00.62
Most Populous4769.49341641539738626764338236611890.870.770.430.6579d 15h160d 8h716.3204.216.0496.13.21:31.00.69

More Data by Country

Click top row to sort:±±±±±±±±±±±±±±±
CountryPop (mio)InfectedActiveDeathsRecoveredDeaths per RecoveredRecovered per
Deaths per infected ... days agoPossible
Total %
absolute values% / ratio0d5d7d10d14d
Most Populous4769.49341641539738626764338236611893.21:31.00.690. Populous

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