COVID-19 - South America - 20-09-22

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 7610000 1768.5 56546 0.75% 0.72%
Active cases 885300 205.7 18660 2.15% -0.58%
Deaths 240445 55.9 1439 0.6% 0.42%
Recovered 64842551506.8364470.57%0.74%
Deaths per infected 3.16%
Recovered per infected85.21%
Active per infected 11.63%
Deaths per recovered 3.71%
Projection:
Total Case Percentage
15.1%

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 92d 22h 96d 17h
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: 189Population na
Total casesCases per 100.000Average grow rate (5 days)
Infected na 14 76
Active na 30 133
Deaths na 14 64
Recovered na 12 63
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!

Diagrams

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
infected
absolute valuesPercentage growthrate 5dTime to doubleCases per 100.000% / ratio
Brazil211.284459136443642813810540168310.6-0.840.340.61115d 5h201d 16h2173.1206.665.41901.23.41:29.10.87
Chile19.10744852313026123214231760.33-1.390.260.34209d 1h271d 7h2347.468.264.52214.72.91:34.40.94
Ecuador17.44912764313665111261028520.87-0.830.121.1980d 7h>1yr731.578.363.8589.510.81:9.20.81
Peru32.131768895129689313696078370.651.850.20.45106d 23h339d 21h2393.0403.697.61891.75.21:19.40.79
Argentina44.939652174120994139525172281.62-2.271.592.243d 0h43d 19h1451.3269.231.01151.02.71:37.00.79
Colombia49.396777537112240243976409000.890.120.610.8278d 11h113d 10h1574.1227.249.41297.53.81:26.20.82
Uruguay3.51919342434616450.61-0.060.00.65113d 19h55.06.91.346.82.81:35.70.85
Venezuela32.2196845310115564577741.26-1.881.311.5455d 3h53d 2h212.531.41.8179.31.01:102.00.84
Bolivia11.47131453329077693908530.31-0.650.380.57222d 4h183d 16h1146.1286.967.1792.18.51:11.80.69
Paraguay7.1533482814866705192572.281.032.982.730d 16h23d 14h486.9207.89.9269.23.71:27.30.55
Guyana0.783243710096713613.768.121.620.8618d 18h43d 0h311.3128.98.6173.94.91:20.30.56
Suriname0.581475911810045410.37-21.160.421.7185d 16h165d 19h818.520.317.2781.02.21:45.50.95
South America430.32761000088530024044564842550.72-0.580.420.7496d 17h166d 22h1768.5205.755.91506.83.71:27.00.85

More Data by Country

Click top row to sort:±±±±±±±±±±±±±±±
CountryPop (mio)InfectedActiveDeathsRecoveredDeaths per RecoveredRecovered per
infected
Deaths per infected ... days agoPossible
Total %
Country
absolute values% / ratio0d5d7d10d14d
Brazil211.284459136443642813810540168313.41:29.10.870.030.030.030.030.0317.67Brazil
Chile19.10744852313026123214231762.91:34.40.940.030.030.030.030.0317.43Chile
Ecuador17.449127643136651112610285210.81:9.20.810.090.090.090.090.117.23Ecuador
Peru32.131768895129689313696078375.21:19.40.790.040.040.040.040.0526.39Peru
Argentina44.939652174120994139525172282.71:37.00.790.020.020.020.030.038.39Argentina
Colombia49.396777537112240243976409003.81:26.20.820.030.030.030.030.0413.35Colombia
Uruguay3.51919342434616452.81:35.70.850.020.020.020.030.030.35Uruguay
Venezuela32.2196845310115564577741.01:102.00.840.010.010.010.010.010.47Venezuela
Bolivia11.47131453329077693908538.51:11.80.690.060.060.060.060.0618.13Bolivia
Paraguay7.1533482814866705192573.71:27.30.550.020.020.020.030.032.66Paraguay
Guyana0.783243710096713614.91:20.30.560.030.030.030.040.042.31Guyana
Suriname0.581475911810045412.21:45.50.950.020.020.020.020.024.65Suriname
South America430.32761000088530024044564842553.71:27.00.850.030.030.030.030.0415.1South 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