COVID-19 - South America - 20-10-09

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 8562711 1989.8 58133 0.68% 0.7%
Active cases 801124 186.2 19074 2.44% 0.3%
Deaths 269098 62.5 1763 0.66% 0.46%
Recovered 74924891741.1372960.5%0.59%
Deaths per infected 3.14%
Recovered per infected87.5%
Active per infected 9.36%
Deaths per recovered 3.59%
Projection:
Total Case Percentage
16.9%

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 101d 18h 100d 1h
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 15 85
Active na 38 100
Deaths na 12 70
Recovered na 12 71
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
Brazil211.284505588840339514963945028540.57-0.10.350.51122d 20h196d 7h2392.9190.970.82131.23.31:30.10.89
Chile19.10747776914252132204502970.32-1.330.290.3216d 9h240d 19h2500.574.669.22356.72.91:34.00.94
Ecuador17.44914584813162121751205110.677.030.840.0103d 4h82d 15h835.975.469.8690.710.11:9.90.83
Peru32.13183861477300330987282160.41-3.230.240.77168d 15h284d 3h2610.0240.6103.02266.44.51:22.00.87
Argentina44.939871468151102232256971411.761.131.561.4739d 14h44d 16h1939.2336.251.71551.33.31:30.00.8
Colombia49.39689430086258274957805470.95.050.350.3277d 5h199d 7h1810.5174.655.71580.23.51:28.40.87
Uruguay3.51922512854919170.971.590.420.6471d 19h166d 16h64.08.11.454.52.61:39.10.85
Venezuela32.219816967992684730200.82-1.670.760.9485d 1h92d 3h253.624.82.1226.60.91:106.40.89
Bolivia11.471382262961782621003470.2-0.840.310.46351d 0h222d 16h1205.1258.272.0874.98.21:12.20.73
Paraguay7.15348275165871045306431.790.351.731.9739d 2h40d 9h674.9231.914.6428.43.41:29.30.63
Guyana0.7833358107810021801.67-0.312.422.4441d 22h29d 0h429.0137.712.8278.54.61:21.80.65
Suriname0.58150189610648160.312.180.00.22224d 2h863.116.518.2828.32.21:45.50.96
South America430.32856271180112426909874924890.70.30.460.59100d 1h150d 4h1989.8186.262.51741.13.61:27.90.88

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
Brazil211.284505588840339514963945028543.31:30.10.890.030.030.030.030.0319.14Brazil
Chile19.10747776914252132204502972.91:34.00.940.030.030.030.030.0318.7Chile
Ecuador17.449145848131621217512051110.11:9.90.830.080.090.090.090.0918.86Ecuador
Peru32.13183861477300330987282164.51:22.00.870.040.040.040.040.0427.84Peru
Argentina44.939871468151102232256971413.31:30.00.80.030.030.030.030.0313.97Argentina
Colombia49.39689430086258274957805473.51:28.40.870.030.030.030.030.0315.04Colombia
Uruguay3.51922512854919172.61:39.10.850.020.020.020.020.020.38Uruguay
Venezuela32.219816967992684730200.91:106.40.890.010.010.010.010.010.57Venezuela
Bolivia11.471382262961782621003478.21:12.20.730.060.060.060.060.0619.47Bolivia
Paraguay7.15348275165871045306433.41:29.30.630.020.020.020.030.033.95Paraguay
Guyana0.7833358107810021804.61:21.80.650.030.030.030.030.043.45Guyana
Suriname0.58150189610648162.21:45.50.960.020.020.020.020.024.93Suriname
South America430.32856271180112426909874924893.61:27.90.880.030.030.030.030.0316.9South 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