Labor am Elm

Elm Laboratory

Consulting and Research

Jens Röder

4 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.

Locations or countries with not enough data points or other reasons are skipped and can be found in this list.

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 500 , between 500 and 999, between 1000 and 9999, between 10000 and 49999, between 50000 and 99999, above 100000.

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: Tue Jun 15 08:11:19 UTC 2021

Click on the down arrow to open content and click on image to enlarge.
Clicking on the name will direct to a page with all images for the country.
Ncurrent
location
Nmax (err) cumulative_inf. infected_daily T2 (err) dturning_point (err)
1883
Ford, Illinois
fiterr (±err) 51.540 (±80.7%) 358.83 (±33.8%)
1763
Edgar, Illinois
2482 (±86.9%) 42.101 (±46.2%) 339.68 (±12.6%)
1646
Osage, Missouri
1505 (±51.5%) 38.715 (±45.0%) 305.17 (±9.1%)
1389
Calhoun, Iowa
1679 (±39.2%) 38.722 (±32.1%) 310.99 (±6.6%)
1205
Custer, Montana
1565 (±17.6%) 43.365 (±11.0%) 324.41 (±3.0%)
1162
Mercer, North Dakota
1189 (±29.0%) 34.222 (±32.3%) 298.12 (±4.7%)
1103
Dawson, Montana
1660 (±4.2%) 43.722 (±2.3%) 333.31 (±0.7%)
1005
Cloud, Kansas
1147 (±51.4%) 33.861 (±42.9%) 321.14 (±6.6%)
661
Hickory, Missouri
591 (±2.8%) 45.117 (±2.2%) 298.79 (±0.6%)
543
Webster, West Virginia
fiterr (±err) 168.534 (±11.5%) 1029.10 (±14.9%)
530
Sheridan, Nebraska
fiterr (±err) 214.976 (±24.8%) 1297.45 (±34.5%)
516
Chouteau, Montana
456 (±2.1%) 34.096 (±1.9%) 314.21 (±0.3%)
424
Sheridan, Montana
400 (±1.3%) 26.696 (±1.7%) 312.84 (±0.1%)
416
Trinity, California
383 (±64.8%) 31.274 (±50.4%) 330.92 (±6.8%)
385
Reagan, Texas
fiterr (±err) 240.749 (±120.5%) 1326.48 (±169.6%)
369
Boise, Idaho
fiterr (±err) 183.009 (±22.7%) 980.85 (±30.1%)
334
Rawlins, Kansas
312 (±2.9%) 38.105 (±2.6%) 304.50 (±0.5%)
332
Hettinger, North Dakota
385 (±2.6%) 43.641 (±2.0%) 304.57 (±0.5%)
331
Collingsworth, Texas
fiterr (±err) fiterr (±err)fiterr (±err)
288
Fallon, Montana
289 (±1.3%) 22.818 (±2.3%) 308.89 (±0.1%)
273
Bath, Virginia
fiterr (±err) 186.884 (±9.3%) 1176.92 (±12.6%)
270
Adams, North Dakota
223 (±1.4%) 30.515 (±1.8%) 300.66 (±0.2%)
266
Haakon, South Dakota
376 (±3.7%) 46.243 (±2.2%) 326.25 (±0.7%)
255
Hitchcock, Nebraska
319 (±111.0%) 43.905 (±58.9%) 338.00 (±17.4%)
220
Brown, Nebraska
295 (±3.2%) 41.527 (±2.4%) 312.07 (±0.6%)
197
Daniels, Montana
161 (±1.8%) 27.413 (±2.3%) 312.17 (±0.2%)
193
Jeff Davis, Texas
40893 (±189.2%) 128.995 (±16.1%) 733.14 (±18.8%)
173
Mora, New Mexico
fiterr (±err) 134.667 (±16.3%) 839.83 (±19.5%)
131
Campbell, South Dakota
113 (±0.6%) 25.802 (±1.2%) 280.00 (±0.1%)
122
Sheridan, North Dakota
113 (±13.4%) 33.753 (±15.2%) 297.73 (±2.2%)
114
Garden, Nebraska
fiterr (±err) 235.599 (±114.5%) 1390.96 (±161.4%)
104
Greeley, Kansas
fiterr (±err) 223.880 (±50.5%) 1341.85 (±70.5%)
97
Harding, South Dakota
87 (±1.4%) 22.213 (±3.0%) 294.84 (±0.2%)
89
Yakutat, Alaska
63 (±9.3%) 48.525 (±9.1%) 259.49 (±3.2%)
84
McMullen, Texas
fiterr (±err) 277.336 (±52.9%) 1605.91 (±75.9%)
80
Garfield, Montana
fiterr (±err) 266.242 (±44.1%) 1603.29 (±63.7%)
75
Gilliam, Oregon
fiterr (±err) 251.419 (±18.0%) 1521.90 (±25.8%)
65
Jackson, Colorado
fiterr (±err) 219.053 (±52.2%) 1188.51 (±72.0%)
54
Hooker, Nebraska
62 (±28.0%) 38.860 (±26.8%) 296.23 (±5.4%)
39
Culebra, Puerto Rico
18 (±0.9%) 17.004 (±4.3%) 198.51 (±0.4%)
36
Banner, Nebraska
fiterr (±err) 121.573 (±53.7%) 703.30 (±60.7%)

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.

Locations or countries with not enough data points or other reasons are skipped and can be found in this list.


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