COVID-19 - South America - 20-06-06

Data from JHU, ca. 9:00 CET

South America is a Group with the following members:
Argentina - Bolivia - Brazil - Chile - Colombia - Ecuador - French Guiana - Guyana - Paraguay - Peru - Suriname - Uruguay - Venezuela

Go to the data tables

absolutecases per 100.000 abs. development
1 day
rel. development
1 day
rel. development
5 days/average
Total infections 1111719 258.3 39641 3.7% 4.28%
Active cases 554763 128.9 -247521 -30.85% 10.64%
Deaths 48755 11.3 1255 2.64% 3.01%
Recovered 508201118.1285907128.62%-6.88%
Deaths per infected 4.39%
Recovered per infected45.71%
Active per infected 49.9%
Deaths per recovered 9.59%
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 19d 2h 16d 13h
Time to reach a million cases
Time to saturate the population164d 2h 142d 7h

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 34 34
Active na 24 7
Deaths na 19 34
Recovered na 42 185
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: South America

Argentina - Bolivia - Brazil - Chile - Colombia - Ecuador - French Guiana - Guyana - Paraguay - Peru - Suriname - Uruguay - Venezuela

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
Brazil211.284672846359767359302771495.0320.193.23.914d 2h21d 23h318.5170.317.0131.213.01:7.70.41
Chile19.1071277452238715411038173.97-4.165.4462.7517d 19h13d 2h668.6117.28.1543.31.51:67.60.81
Ecuador17.44942728181003608210201.81.611.030.9838d 21h67d 13h244.9103.720.7120.517.21:5.80.49
Peru32.1311917581037265301827312.451.262.22.9728d 16h31d 19h596.8322.816.5257.56.41:15.60.43
Argentina44.939220201519264861804.84.812.611.9814d 18h26d 22h49.033.81.413.810.51:9.50.28
Colombia49.39636759218851204136704.631.854.6110.4215d 7h15d 8h74.444.32.427.78.81:11.40.37
Uruguay3.51984596237260.48-4.380.00.91144d 9h24.02.70.720.63.21:31.50.86
Venezuela32.21923161909223856.895.993.42.1210d 9h20d 17h7.
Bolivia11.47133581100245419024.873.154.539.0314d 13h15d 15h116.595.94.016.623.91:4.20.14
Paraguay7.1531090547115321.862.510.01.1337d 14h15.
Suriname0.581100901918.2919.70.00.04d 3h17.
South America430.321111719554763487555082014.2810.643.01-6.8816d 13h23d 8h258.3128.911.3118.19.61:10.40.46

More Data by Country

Click top row to sort:±±±±±±±±±±±±±±±
CountryPop (mio)InfectedActiveDeathsRecoveredDeaths per RecoveredRecovered per
Deaths per infected ... days agoPossible
Total %
absolute values% / ratio0d5d7d10d14d
South America430.321111719554763487555082019.61:10.40.460. America

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