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Elm Laboratory

Consulting and Research

COVID-19 Regional Numbers of Dead People

fit with advanced Gompertz function

Jens Röder

8 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 dead people: Below 30 , between 30 and 99, between 100 and 499, between 500 and 999, between 1000 and 4999, above 5000.

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: Thu Dec 3 05:16:07 UTC 2020

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Ncurrent
location
Nmax (err) cumulative_dead death rate (err) death_rate deaths_daily T2 (err) dturning_point (err)
1480502
World total, World total
1602109 (±1.7%) 4.33 (±5.1%) 53.174 (±1.6%) 200.26 (±1.0%)
1475759
World without China, World without China
1606889 (±1.7%) 4.30 (±5.1%) 53.462 (±1.6%) 201.39 (±1.1%)
406126
North America, North America
401110 (±1.2%) 5.44 (±5.1%) 45.788 (±1.5%) 175.04 (±0.8%)
311285
South America, South America
330716 (±0.3%) 4.51 (±3.1%) 42.058 (±0.4%) 205.77 (±0.1%)
275750
Europe, Europe
163206 (±1.4%) 14.48 (±3.5%) 22.779 (±5.0%) 104.58 (±2.0%)
270642
USA, USA
251128 (±1.4%) 5.45 (±5.2%) 42.965 (±2.1%) 156.40 (±1.1%)
173817
Brazil
175226 (±0.4%) 4.17 (±2.8%) 38.675 (±0.6%) 188.84 (±0.2%)
156458
South Asia, South Asia
184110 (±0.4%) 2.50 (±4.3%) 44.854 (±0.4%) 232.96 (±0.1%)
91996
Middle East, Middle East
156483 (±3.6%) 5.02 (±4.2%) 70.412 (±1.8%) 277.18 (±1.6%)
56361
Italy
37441 (±0.8%) 18.77 (±2.4%) 17.280 (±3.6%) 95.20 (±1.1%)
54178
East Europe, East Europe
148875 (±12.6%) 4.68 (±3.1%) 83.387 (±4.3%) 349.34 (±4.4%)
52049
Africa, Africa
55145 (±0.9%) 3.20 (±1.5%) 44.497 (±1.0%) 217.51 (±0.4%)
45511
Spain
31794 (±1.0%) 12.33 (±3.5%) 16.305 (±4.7%) 96.86 (±1.3%)
38928
Argentina
58830 (±2.2%) 3.65 (±3.2%) 45.497 (±1.5%) 282.05 (±0.5%)
25954
South-East Asia, South-East Asia
41562 (±1.2%) 3.59 (±6.7%) 60.604 (±0.7%) 268.47 (±0.5%)
21644
South Africa
21080 (±0.5%) 2.91 (±1.3%) 32.812 (±0.9%) 211.48 (±0.2%)
17081
Indonesia
25358 (±0.8%) 4.33 (±2.9%) 58.569 (±0.5%) 261.23 (±0.3%)
16786
Belgium
10768 (±1.1%) 18.08 (±3.5%) 15.534 (±5.6%) 105.36 (±1.3%)
13501
Ecuador
17095 (±3.2%) 7.30 (±4.4%) 52.432 (±2.9%) 214.26 (±1.7%)
12229
Canada, Canada
9725 (±0.6%) 8.82 (±2.3%) 20.118 (±2.3%) 123.65 (±0.6%)
8963
Bolivia
9635 (±0.8%) 6.44 (±0.6%) 33.441 (±1.4%) 218.39 (±0.3%)
8418
Philippines
14450 (±2.9%) 0.87 (±22.5%) 60.423 (±1.6%) 274.39 (±1.1%)
7385
East Asia, East Asia
6526 (±0.6%) 5.66 (±2.0%) 23.529 (±2.1%) 65.14 (±1.7%)
6675
Bangladesh
6746 (±0.4%) 2.20 (±2.6%) 39.587 (±0.6%) 200.51 (±0.2%)
6666
Egypt
6327 (±0.4%) 6.18 (±1.0%) 28.712 (±0.9%) 173.12 (±0.2%)
4743
China total, China total
4684 (±0.4%) 5.51 (±0.6%) 16.078 (±2.1%) 51.28 (±1.4%)
4512
Hubei, China
4504 (±0.4%) fiterr (±err) 15.939 (±2.1%) 51.10 (±1.4%)
4188
Bulgaria
652313075 (±610.2%) 9.64 (±9.1%) 189.178 (±23.1%) 1146.66 (±31.9%)
3325
Austria
52171466 (±1492.1%) 13.42 (±3.4%) 283.626 (±72.2%) 1579.23 (±105.2%)
3260
Tunisia
8484 (±6.5%) 2.63 (±15.8%) 39.505 (±2.5%) 331.84 (±0.8%)
3098
Panama
3150 (±0.7%) 2.48 (±6.6%) 40.288 (±0.9%) 203.29 (±0.3%)
2918
Honduras
3046 (±0.4%) 3.42 (±3.7%) 37.669 (±0.6%) 208.95 (±0.2%)
2877
Israel
8271 (±9.6%) 1.46 (±43.8%) 70.988 (±3.6%) 331.04 (±3.0%)
2727
Bosnia and Herzegovina
72330171 (±285.3%) 1.66 (±44.8%) 200.456 (±13.3%) 1161.35 (±18.4%)
2517
Greece
354673080 (±903.4%) fiterr (±err) 171.983 (±34.4%) 1056.06 (±46.4%)
2447
Algeria
2522 (±1.5%) 4.98 (±4.8%) 51.631 (±1.7%) 186.97 (±1.0%)
2434
Kazakhstan
2286 (±0.4%) 1.50 (±9.6%) 24.222 (±1.2%) 210.78 (±0.2%)
2333
Dominican Republic
2641 (±1.0%) 2.75 (±5.6%) 43.980 (±1.3%) 193.53 (±0.5%)
2323
Moldova
3986 (±4.2%) 4.24 (±4.3%) 68.367 (±2.1%) 279.80 (±1.8%)
2193
Armenia
5447 (±20.7%) 3.78 (±2.6%) 82.507 (±7.3%) 341.95 (±7.5%)
1797
Afghanistan
1565 (±0.5%) 4.62 (±0.7%) 26.410 (±1.3%) 169.74 (±0.3%)
1792
North Macedonia
33545 (±64.5%) 5.80 (±9.1%) 128.626 (±10.0%) 593.06 (±13.0%)
1771
Paraguay
2027 (±0.4%) 0.85 (±41.7%) 34.612 (±0.4%) 268.29 (±0.1%)
1709
Ethiopia
1758 (±0.6%) 1.95 (±13.9%) 34.549 (±0.8%) 235.73 (±0.2%)
1490
Slovenia
101904239 (±778.3%) fiterr (±err) 131.839 (±32.5%) 837.75 (±40.4%)
1474
Kenya
3433 (±8.6%) fiterr (±err) 71.253 (±3.3%) 323.25 (±2.8%)
1433
Azerbaijan
2241 (±14.8%) 1.74 (±12.8%) 71.814 (±6.6%) 299.27 (±5.9%)
1430
Oman
1739 (±0.9%) 1.06 (±8.9%) 46.883 (±0.8%) 240.37 (±0.3%)
1196
Libya
1759 (±0.9%) 1.36 (±13.4%) 46.307 (±0.6%) 285.18 (±0.2%)
1176
Nigeria
1160 (±0.1%) 2.87 (±5.2%) 29.474 (±0.3%) 165.66 (±0.1%)
1166
Belarus
1232 (±1.2%) 1.83 (±4.0%) 48.749 (±1.4%) 199.34 (±0.7%)
1033
Lebanon
3537 (±5.8%) fiterr (±err) 65.718 (±1.8%) 355.85 (±1.3%)
942
Australia - Oceania, Australia - Oceania
980 (±1.2%) 6.53 (±3.6%) 24.847 (±3.0%) 219.71 (±0.4%)
846
Denmark
657 (±0.6%) 4.73 (±3.1%) 16.900 (±2.9%) 102.56 (±0.8%)
822
Albania
1740 (±7.1%) 2.02 (±43.1%) 69.758 (±2.8%) 320.19 (±2.3%)
576
United Arab Emirates
489 (±1.4%) fiterr (±err) 36.427 (±3.0%) 142.84 (±1.3%)
551
Alberta, Canada
4547 (±70.7%) 4.44 (±3.5%) 136.045 (±14.6%) 549.77 (±20.6%)
526
Korea - South
576 (±4.8%) 3.64 (±2.3%) 62.193 (±5.5%) 141.35 (±5.7%)
519
Lithuania
46027252 (±1196.2%) fiterr (±err) 228.920 (±47.6%) 1345.46 (±67.9%)
457
British Columbia, Canada
331 (±4.1%) 9.09 (±4.7%) 52.765 (±5.3%) 150.52 (±3.7%)
441
Cameroon
428 (±0.2%) 2.05 (±4.0%) 25.310 (±0.7%) 143.97 (±0.2%)
422
Syria
649 (±2.4%) 6.17 (±4.9%) 51.347 (±1.3%) 287.55 (±0.6%)
363
Malaysia
2709235 (±1104.8%) 3.75 (±3.2%) 299.969 (±61.6%) 1616.36 (±90.3%)
350
Angola
534 (±1.5%) 4.34 (±6.1%) 49.769 (±1.0%) 276.77 (±0.4%)
341
Bahrain
397 (±1.4%) 0.65 (±11.5%) 45.429 (±1.4%) 219.27 (±0.6%)
335
Congo (Kinshasa)
319 (±0.6%) 3.08 (±2.6%) 35.628 (±1.1%) 168.53 (±0.4%)
334
Norway
267 (±0.5%) 3.29 (±3.2%) 14.521 (±2.7%) 99.82 (±0.6%)
330
Luxembourg
7366 (±354.1%) 5.66 (±3.3%) 199.192 (±52.8%) 841.17 (±79.9%)
328
Manitoba, Canada
56438397 (±335.4%) 3.37 (±32.1%) 124.351 (±12.7%) 813.06 (±15.6%)
258
Jamaica
287 (±1.6%) fiterr (±err) 30.182 (±1.9%) 274.48 (±0.3%)
251
Madagascar
248 (±0.3%) 1.75 (±9.0%) 24.980 (±0.8%) 208.55 (±0.1%)
233
Haiti
236 (±0.2%) 3.01 (±2.3%) 29.307 (±0.4%) 173.84 (±0.1%)
210
Latvia
9152947 (±943.3%) 13.48 (±3.3%) 205.544 (±40.8%) 1203.96 (±56.9%)
205
Uganda
526 (±16.5%) 4.21 (±16.3%) 59.997 (±6.1%) 336.53 (±3.7%)
163
Bahamas
216 (±3.2%) 3.81 (±5.9%) 40.672 (±2.7%) 266.07 (±0.8%)
161
Nicaragua
157 (±0.3%) 3.78 (±5.8%) 29.033 (±0.7%) 169.43 (±0.2%)
160
Mali
133 (±0.4%) 6.03 (±2.8%) 21.906 (±1.3%) 135.40 (±0.3%)
151
Guyana
322 (±7.1%) 1.95 (±33.6%) 59.470 (±3.3%) 304.25 (±2.1%)
149
Guadeloupe, France
178 (±4.1%) fiterr (±err) 30.240 (±4.6%) 277.30 (±0.6%)
148
Belize
6577931 (±197.7%) 5.91 (±5.9%) 154.201 (±8.7%) 940.46 (±11.3%)
141
Malta
7855928 (±293.9%) 5.95 (±15.7%) 173.777 (±12.6%) 1043.11 (±17.0%)
120
Trinidad and Tobago
122 (±1.5%) fiterr (±err) 26.933 (±2.6%) 254.69 (±0.3%)
114
Congo (Brazzaville)
98 (±1.1%) 2.12 (±7.7%) 34.577 (±2.0%) 178.29 (±0.6%)
106
Cabo Verde
182 (±3.7%) 2.35 (±10.2%) 56.303 (±2.1%) 277.02 (±1.2%)
83
Liberia
86 (±0.9%) 5.45 (±3.1%) 30.571 (±2.2%) 158.36 (±0.7%)
76
Andorra
58 (±1.0%) 6.73 (±3.2%) 16.303 (±5.6%) 99.41 (±1.4%)
75
Niger
69 (±0.1%) 7.04 (±1.3%) 16.039 (±0.7%) 114.48 (±0.1%)
74
Sierra Leone
265014 (±3857.3%) 3.89 (±2.1%) 410.713 (±258.4%) 2096.99 (±388.1%)
68
Burkina Faso
58 (±0.6%) 5.84 (±3.2%) 15.636 (±3.4%) 98.66 (±0.8%)
65
Nova Scotia, Canada
64 (±0.1%) 6.05 (±0.8%) 12.076 (±0.8%) 118.10 (±0.1%)
64
Togo
109414117 (±967.0%) 3.34 (±9.3%) 325.768 (±30.9%) 1941.70 (±46.1%)
63
Central African Republic
62 (±0.3%) 1.19 (±13.4%) 13.026 (±1.6%) 171.18 (±0.1%)
61
Djibouti
61 (±0.2%) 1.58 (±5.9%) 16.378 (±0.8%) 152.20 (±0.1%)
53
New South Wales, Australia
51 (±0.3%) 1.40 (±4.3%) 15.738 (±1.3%) 99.53 (±0.3%)
49
Mayotte, France
43 (±0.5%) 1.77 (±8.2%) 25.023 (±1.6%) 140.07 (±0.5%)
48
Channel Islands, United Kingdom
47 (±0.2%) 7.53 (±1.2%) 11.472 (±1.1%) 106.36 (±0.2%)
46
San Marino
42 (±0.1%) 6.32 (±1.9%) 10.653 (±1.0%) 81.87 (±0.2%)
45
Aruba, Netherlands
50 (±2.0%) fiterr (±err) 32.533 (±2.5%) 257.41 (±0.4%)
44
Guinea-Bissau
43 (±0.7%) 1.51 (±28.2%) 32.428 (±1.5%) 171.81 (±0.4%)
43
Benin
42 (±0.3%) 2.11 (±18.5%) 20.496 (±1.2%) 177.74 (±0.2%)
41
Martinique, France
100721 (±768.5%) fiterr (±err) 282.302 (±50.1%) 1473.80 (±73.3%)
40
Reunion, France
678 (±48.5%) 4.95 (±4.6%) 100.533 (±8.0%) 506.67 (±8.7%)
35
Vietnam
35 (±0.3%) 6.62 (±3.6%) 13.341 (±1.4%) 221.42 (±0.1%)
34
Botswana
41 (±2.9%) fiterr (±err) 39.754 (±2.3%) 274.45 (±0.6%)
25
Sint Maarten, Netherlands
31 (±7.8%) fiterr (±err) 74.229 (±8.9%) 124.93 (±12.3%)

For countries in this list, the number of dead 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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