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Elm Laboratory

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COVID-19 Continental Numbers of Infected People

fit with advanced Gompertz function

Jens Röder

3 minutes read

with Advanced Gompertz Function

All the fits of the data of individual areas are created fully automatically. You may check on the graph (click on the image) if the fit has a sufficient quality, matching the data points as best as possible. There may be some cases, where by too unexpected real data, the fit is not giving a good forecast. So please use common sense to evaluate the data.

The table shows from the left: The maximum last cumulative number, the expected maximum number by fit, graph and location, the T2 also known as doubling time of the exponential growth, the day of turning point of the function.

The turning point is important, showing the turn from purely exponential growth to the process of fading out by limited number of victims.

In the middle of the graph is written the doubling time, that describes the time it needs to double the number of cases. This number is calculated using the logistic function and describes the growth before the turning point, where numbers rise quickly. In a simple picture, the T2 of the Gompertz function describes the later part and the doubling time of the logisitic the first part.

Color code on numbers of infected people: Below 10000 , between 10000 and 49999, between 50000 and 49999, between 100000 and 499999, between 500000 and 999999, above 1000000.

Color code on locations describe percentages of last number and expected Nmax: Above 95%, between 90% and 95%, between 80% and 89%, between 70% and 79%, between 60% and 69%, when number of cases is above 50 and Nmax is below 50% or the doubling time is below 3.5 days! Above 130%, a reoccurrence of an outbreak is indicated.

The location color code tells you, how well the Covid-19 outbreak has faded out and is under control (greenish). In red and magenta the areas are on fast rise in numbers. The color code in numbers tells you how severe the outbreak was in that region.

Applied maths is explained here.


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Actualisation date: Wed Dec 2 05:26:05 UTC 2020

Click on the down arrow to open content and click on image to enlarge.
Ncurrent
location
Nmax (err) cumulative_inf. infected_daily T2 (err) dturning_point (err)
63236804
World total
132192427 (±3.4%) 71.828 (±1.4%) 307.79 (±1.3%)
63143902
World without China
131041631 (±3.4%) 71.490 (±1.4%) 306.99 (±1.3%)
15802754
North America
22764793 (±3.8%) 64.591 (±2.1%) 263.88 (±1.7%)
11921118
Europe
7700807676190 (±514.6%) 222.098 (±17.3%) 1347.24 (±24.8%)
10855167
South America
11810956 (±0.4%) 43.547 (±0.4%) 218.57 (±0.2%)
10645581
South Asia
13078881 (±0.5%) 44.157 (±0.5%) 247.15 (±0.2%)
3866107
Middle East
5316771 (±2.7%) 62.813 (±1.6%) 252.65 (±1.3%)
3164926
East Europe
9128050 (±14.8%) 86.971 (±4.8%) 357.66 (±5.2%)
2162295
Africa
2152261 (±1.0%) 41.470 (±1.3%) 210.82 (±0.4%)
1098981
South-East Asia
1690100 (±0.8%) 57.749 (±0.5%) 267.75 (±0.3%)
277992
East Asia
493074 (±13.1%) 97.510 (±7.1%) 253.66 (±11.4%)
92902
China total
86834 (±0.2%) 6.359 (±2.3%) 37.46 (±0.7%)
30691
Australia - Oceania
35906 (±2.5%) 46.225 (±3.2%) 176.22 (±1.6%)

For countries in this list, the number of infected people must be at minimum 13 people. In the list of numbers of a country, there must be at least 7 different numbers. The turning point is guessed by using half the maximum number and then looks for the first value above that value. If the turning point is at the last value, the fit is omitted.

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