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Elm Laboratory

Consulting and Research

COVID-19 Regional Numbers of Infected People

fit with advanced Gompertz function

Jens Röder

7 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.

The color code on locations describes 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 color code on turning, that is: More than 20 days passed, more than 10 days passed, more than 5 days passed, ahead 5 days, ahead 10 days, more than 10 days ahead.

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: Thu Dec 3 05:24:26 UTC 2020

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Ncurrent
location
Nmax (err) cumulative_inf. infected_daily T2 (err) dturning_point (err)
6386787
Brazil
6461877 (±0.4%) 39.897 (±0.5%) 207.77 (±0.2%)
1656444
Spain
7990030812 (±181.9%) 206.680 (±10.6%) 1136.92 (±14.8%)
1643086
United Kingdom
296353101269 (±553.6%) 239.645 (±21.1%) 1412.20 (±30.4%)
1432570
Argentina
2136780 (±0.8%) 48.362 (±0.5%) 275.95 (±0.2%)
543975
Indonesia
1071865 (±1.3%) 63.317 (±0.6%) 301.73 (±0.4%)
467225
Bangladesh
447485 (±0.5%) 36.905 (±0.9%) 192.34 (±0.3%)
387052
Canada, Canada
107302 (±0.2%) 17.896 (±0.4%) 112.45 (±0.1%)
285489
Austria
16147 (±0.4%) 9.354 (±1.4%) 85.10 (±0.2%)
193673
Ecuador
230505 (±1.5%) 53.820 (±1.3%) 214.68 (±0.8%)
148775
Bulgaria
47417880896 (±472.1%) 164.031 (±17.0%) 1024.25 (±22.7%)
144810
Bolivia
147324 (±0.2%) 29.889 (±0.4%) 196.20 (±0.1%)
144302
Dominican Republic
144821 (±0.5%) 39.108 (±0.8%) 199.77 (±0.2%)
140172
Costa Rica
807 (±1.1%) 12.629 (±3.1%) 87.82 (±0.4%)
139343
Georgia
996855 (±6.7%) 49.417 (±1.5%) 374.48 (±0.7%)
138219
Belarus
109345 (±2.5%) 42.984 (±3.7%) 164.86 (±1.8%)
135967
Armenia
15761880 (±128.0%) 152.573 (±13.3%) 763.33 (±17.7%)
125602
Azerbaijan
8156539 (±163.9%) 150.073 (±18.2%) 738.62 (±24.2%)
116303
Egypt
106805 (±0.3%) 23.938 (±0.9%) 161.19 (±0.2%)
92993
China total, China total
86857 (±0.2%) 6.363 (±2.3%) 37.46 (±0.7%)
89085
Bosnia and Herzegovina
1189080475 (±184.6%) 184.817 (±9.4%) 1063.35 (±12.8%)
87137
Bahrain
96928 (±0.7%) 44.098 (±0.9%) 205.24 (±0.3%)
84169
Kenya
176859 (±13.4%) 69.451 (±5.6%) 314.95 (±4.5%)
84152
Algeria
14382 (±1.4%) 22.825 (±1.1%) 127.96 (±0.4%)
67169
Malaysia
16586689990 (±690.0%) 210.522 (±25.3%) 1266.49 (±35.6%)
62945
North Macedonia
2869876069 (±316.9%) 208.569 (±13.9%) 1215.57 (±19.5%)
59484
Alberta, Canada
7442 (±1.4%) 13.650 (±2.3%) 107.84 (±0.3%)
46717
Afghanistan
40527 (±0.4%) 21.604 (±1.3%) 150.92 (±0.3%)
39014
Albania
4078476 (±54.2%) 134.962 (±5.7%) 697.37 (±7.1%)
35163
Korea - South
53193 (±9.7%) 81.164 (±5.5%) 242.50 (±7.0%)
35129
Luxembourg
8045317598 (±756.4%) 237.892 (±28.0%) 1411.33 (±40.2%)
33894
British Columbia, Canada
2630 (±0.7%) 15.149 (±1.4%) 93.32 (±0.3%)
24487
Cameroon
22241 (±0.4%) 29.835 (±1.0%) 161.27 (±0.3%)
17341
Madagascar
12234629478 (±2500.9%) 325.261 (±88.2%) 1906.53 (±131.2%)
17107
Manitoba, Canada
297 (±0.6%) 9.098 (±2.6%) 90.60 (±0.3%)
15251
Angola
52276 (±7.3%) 62.423 (±2.4%) 348.43 (±1.6%)
14559
French Polynesia, France
60 (±0.4%) 9.439 (±1.5%) 84.77 (±0.2%)
12859
Congo (Kinshasa)
11337 (±0.4%) 27.756 (±1.1%) 161.35 (±0.3%)
12497
Estonia
539087265 (±822.5%) 247.054 (±35.7%) 1418.72 (±51.3%)
11240
French Guiana, France
35310811 (±471.1%) 70.163 (±22.4%) 431.35 (±28.1%)
10816
Cabo Verde
18675 (±1.5%) 58.689 (±0.8%) 282.95 (±0.5%)
10742
Botswana
80831 (±17.3%) 77.021 (±3.8%) 413.86 (±3.3%)
9296
Haiti
8810 (±0.4%) 22.649 (±1.2%) 161.19 (±0.2%)
8745
Saskatchewan, Canada
1781455461 (±743.2%) 223.457 (±27.4%) 1334.65 (±39.0%)
8381
Cuba
2024 (±0.3%) 12.960 (±0.5%) 104.44 (±0.1%)
7543
Bahamas
9314 (±1.0%) 37.851 (±1.0%) 262.56 (±0.2%)
6790
Andorra
805 (±0.6%) 10.434 (±2.2%) 88.66 (±0.3%)
5854
Belize
13627 (±5.3%) 54.969 (±2.1%) 324.61 (±1.1%)
5774
Congo (Brazzaville)
5629 (±0.5%) 31.636 (±1.1%) 192.56 (±0.2%)
4918
Central African Republic
4833 (±0.1%) 18.053 (±0.6%) 160.43 (±0.1%)
4588
New South Wales, Australia
3060 (±0.2%) 7.622 (±1.0%) 85.14 (±0.1%)
3015
Benin
2745 (±0.8%) 31.824 (±1.7%) 182.61 (±0.4%)
2997
Togo
935 (±8.5%) 25.436 (±4.8%) 144.50 (±2.2%)
2931
Burkina Faso
6979 (±11.6%) 88.372 (±4.9%) 313.00 (±5.8%)
2503
Curacao, Netherlands
29 (±3.5%) 29.956 (±5.5%) 101.52 (±2.3%)
2441
Guinea-Bissau
2344 (±0.5%) 26.089 (±1.5%) 142.05 (±0.5%)
2413
Sierra Leone
1355 (±2.4%) 17.306 (±1.8%) 138.16 (±0.4%)
2137
Lesotho
2220 (±0.8%) 34.012 (±1.3%) 228.48 (±0.3%)
1992
Guangdong, China
1708 (±0.6%) 10.822 (±4.5%) 32.86 (±3.4%)
1650
San Marino
7243 (±124.3%) 147.829 (±33.4%) 509.36 (±53.1%)
1333
Shanghai, China
1686 (±5.7%) 75.259 (±5.0%) 156.53 (±7.5%)
1315
Nova Scotia, Canada
1092 (±0.3%) 11.904 (±1.7%) 100.60 (±0.3%)
1205
Queensland, Australia
1109 (±0.3%) 8.825 (±2.9%) 84.20 (±0.4%)
992
Anhui, China
992 (±0.0%) 4.597 (±0.4%) 33.03 (±0.1%)
823
Western Australia, Australia
667 (±0.7%) 13.075 (±4.0%) 87.58 (±0.9%)
689
Burundi
628 (±1.1%) 35.022 (±1.9%) 192.73 (±0.5%)
680
Jiangsu, China
638 (±0.3%) 4.898 (±1.2%) 33.05 (±0.2%)
613
Comoros
552 (±1.0%) 32.841 (±2.1%) 173.54 (±0.6%)
590
Chongqing, China
578 (±0.4%) 4.917 (±1.2%) 30.77 (±0.3%)
577
Eritrea
22080698 (±1001.1%) 286.804 (±46.9%) 1606.60 (±68.4%)
503
Faroe Islands, Denmark
187 (±0.1%) 6.271 (±0.9%) 79.23 (±0.1%)
500
Shaanxi, China
246 (±0.2%) 4.647 (±0.8%) 31.37 (±0.2%)
490
Fujian, China
296 (±0.3%) 4.670 (±1.0%) 30.36 (±0.2%)
414
Bhutan
522 (±2.1%) 50.157 (±1.7%) 241.96 (±0.8%)
373
Hebei, China
347 (±0.3%) 6.213 (±3.0%) 34.85 (±0.9%)
339
Newfoundland and Labrador, Canada
273 (±0.4%) 7.450 (±3.8%) 87.67 (±0.4%)
329
Inner Mongolia, China
275 (±0.6%) 26.819 (±1.9%) 79.81 (±1.4%)
329
Cambodia
323 (±1.9%) 44.252 (±2.9%) 142.41 (±1.8%)
300
Tianjin, China
193 (±0.8%) 14.415 (±3.4%) 36.95 (±3.1%)
289
Liaoning, China
361 (±4.2%) 66.849 (±5.0%) 112.40 (±7.7%)
285
Cayman Islands, United Kingdom
3265553 (±2466.4%) 377.194 (±136.8%) 2013.99 (±203.8%)
278
Barbados
91 (±0.7%) 10.968 (±2.6%) 89.81 (±0.4%)
263
Guangxi, China
256 (±0.1%) 5.345 (±0.7%) 31.51 (±0.2%)
259
Saint Lucia
2809576 (±557.3%) 125.258 (±29.1%) 775.57 (±35.0%)
231
Tasmania, Australia
230 (±0.1%) 11.010 (±1.0%) 94.07 (±0.2%)
221
Shanxi, China
133 (±0.4%) 4.329 (±1.5%) 31.54 (±0.3%)
182
Gansu, China
164 (±0.6%) 18.162 (±3.4%) 37.86 (±4.5%)
182
Nunavut, Canada
190 (±2.4%) 9.692 (±3.8%) 323.57 (±0.1%)
151
Brunei
143 (±0.2%) 7.467 (±1.5%) 76.48 (±0.2%)
147
Guizhou, China
147 (±0.1%) 4.473 (±0.9%) 34.71 (±0.2%)
142
Antigua and Barbuda
144 (±2.1%) 45.419 (±2.7%) 180.36 (±1.3%)
117
Australian Capital Territory, Australia
111 (±0.2%) 6.988 (±2.0%) 84.70 (±0.2%)
85
Saint Vincent and the Grenadines
85 (±1.5%) 44.461 (±2.0%) 174.67 (±1.0%)
85
Dominica
5089827 (±1052.5%) 277.114 (±45.2%) 1582.09 (±65.8%)
53
Northern Territory, Australia
33 (±1.0%) 9.742 (±7.7%) 87.17 (±1.1%)
47
Yukon, Canada
11 (±0.5%) 10.261 (±2.7%) 90.26 (±0.4%)
46
Macau, China
46 (±0.5%) 14.339 (±2.7%) 69.30 (±1.0%)
39
Laos
19 (±0.5%) 7.913 (±2.6%) 89.11 (±0.3%)

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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