COVID-19 - South America - 20-11-27

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 10971639 2549.6 60440 0.55% 0.5%
Active cases 781435 181.6 16096 2.1% 0.75%
Deaths 322716 75.0 1193 0.37% 0.28%
Recovered 98674882293.1431510.44%0.37%
Deaths per infected 2.94%
Recovered per infected89.94%
Active per infected 7.12%
Deaths per recovered 3.27%
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 125d 11h 138d 4h
Time to reach a million cases
Time to saturate the population>1yr 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: 192Population na
Total casesCases per 100.000Average grow rate (5 days)
Infected na 36 112
Active na 63 79
Deaths na 19 92
Recovered na 24 96
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
Brazil211.284623835048494017197455814360.541.410.270.36127d 17h259d 2h2952.6229.581.42641.73.11:32.50.89
Chile19.1075472439706152785222590.24-0.530.220.2285d 11h315d 23h2864.150.880.02733.32.91:34.10.95
Ecuador17.44918953412167133581640090.425.150.170.0167d 0h>1yr1086.269.776.6940.08.11:12.30.87
Argentina44.93914072771338043821612352570.53-0.440.50.52130d 9h138d 4h3131.5297.785.02748.83.11:32.40.88
Colombia49.3961290510647973621411894990.670.20.410.53104d 12h168d 16h2612.6131.273.32408.13.01:32.90.92
Uruguay3.519530311227441072.451.520.831.828d 15h83d 12h150.731.92.1116.71.81:55.60.77
Venezuela32.2191015244234888964020.34-1.530.30.36206d 13h233d 19h315.113.12.8299.20.91:108.70.95
Paraguay7.15380436217251720569911.010.950.560.7368d 15h123d 19h1124.6303.724.0796.83.01:33.10.71
Guyana0.783531088914942720.68-1.850.831.15102d 5h83d 23h678.3113.619.0545.73.51:28.70.8
South America430.321097163978143532271698674880.50.750.280.37138d 4h247d 14h2549.6181.675.02293.13.31:30.60.9

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 America430.321097163978143532271698674883.31: 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