COVID-19 - Flatliners - 20-09-22

Data from JHU, ca. 9:00 CET

Flatliners is a Group with the following members:
China - Japan - Korea, South - Kuwait - Singapore - Taiwan

Go to the data tables

absolutecases per 100.000 abs. development
1 day
rel. development
1 day
rel. development
5 days/average
Total infections 352207 21.9 1179 0.34% 0.33%
Active cases 18449 1.1 1 0.01% -1.6%
Deaths 7266 0.5 4 0.06% 0.14%
Recovered 32649220.311740.36%0.38%
Deaths per infected 2.06%
Recovered per infected92.7%
Active per infected 5.24%
Deaths per recovered 2.23%
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 206d 17h 209d 7h
Time to reach a million cases 311d 5h315d 3h
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: 189Population na
Total casesCases per 100.000Average grow rate (5 days)
Infected na 156 121
Active na 160 152
Deaths na 151 98
Recovered na 148 94
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: Flatliners

China - Japan - Korea, South - Kuwait - Singapore - Taiwan

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
Korea, South51.781232162178388206500.38-2.860.580.67184d 1h120d 7h44.84.20.739.91.91:53.20.89
Japan126.017977370401519712140.58-0.550.370.62119d 5h185d 23h63.
Kuwait4.421006838483588916120.58-1.970.350.68120d 7h200d 17h2277.8191.913.32072.60.61:156.20.91
Taiwan23.6045092374790. 22h2.
Flatliners1608.953522071844972663264920.33- 7h>1yr21.91.10.520.32.21:44.80.93

More Data by Country

Click top row to sort:±±±±±±±±±±±±±±±
CountryPop (mio)InfectedActiveDeathsRecoveredDeaths per RecoveredRecovered per
Deaths per infected ... days agoPossible
Total %
absolute values% / ratio0d5d7d10d14d
Korea, South51.781232162178388206501.91:53.20.890., South

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