COVID-19 - Thailand - 20-03-30

Data from JHU, ca. 9:00 CET
absolutecases per 100.000 abs. development
1 day
rel. development
1 day
rel. development
5 days/average
Total infections 1388 2.088 143 11.5% 8.5%
Active cases 1152 1.733 10 0.9% 5.7%
Deaths 7 0.011 1 16.7% 10.0%
Recovered 2290.344132136.1%14.1%

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 6d 8h 8d 11h
Time to reach a million cases 60d 10h80d 15h
Time to saturate the population99d 0h 132d 2h

Deaths per infected 0.5%
Recovered per infected16.5%
Active per infected 83.0%
Deaths per recovered 3.1%

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: 174Population 23
Total casesCases per 100.000Average grow rate (5 days)
Infected 36 88 133
Active 39 88 134
Deaths 62 80 65
Recovered 62 51 47
The ranking is made over all registered countries, including small or recent that are ommitted in the table on the front page - which may lead to minor discrepancies between both!

Total Cases

Cases per 100.000

Percentage development

Absolute development (first) with second derivative