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Elm Laboratory

Consulting and Research

COVID-19 Regional Numbers of Infected People

fit with advanced Gompertz function

Jens Röder

6 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: Sun Jan 17 05:25:38 UTC 2021

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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)
8393492
Brazil
7547549 (±0.9%) 46.200 (±1.1%) 220.56 (±0.4%)
1783047
Argentina
1911191 (±0.5%) 45.217 (±0.5%) 268.07 (±0.1%)
700538
Canada, Canada
107302 (±0.2%) 17.896 (±0.4%) 112.45 (±0.1%)
526485
Bangladesh
494898 (±0.7%) 41.391 (±1.2%) 200.20 (±0.4%)
243286
Lebanon
298734 (±0.9%) 53.186 (±0.5%) 323.84 (±0.2%)
226866
Ecuador
246793 (±1.1%) 56.353 (±1.0%) 222.26 (±0.6%)
226549
Azerbaijan
51281961178 (±492.5%) 223.673 (±18.3%) 1345.76 (±25.7%)
221604
Belarus
789812 (±35.9%) 116.718 (±9.9%) 453.69 (±12.9%)
211503
Bulgaria
46522464676 (±458.8%) 201.704 (±17.4%) 1226.42 (±23.8%)
188969
Dominican Republic
163090 (±0.8%) 44.298 (±1.1%) 209.27 (±0.4%)
184187
Costa Rica
807 (±1.1%) 12.629 (±3.1%) 87.82 (±0.4%)
183589
Bolivia
148953 (±0.2%) 30.401 (±0.5%) 196.71 (±0.1%)
163972
Armenia
1006661 (±22.2%) 103.114 (±5.3%) 463.60 (±5.9%)
154620
Egypt
112265 (±0.5%) 26.535 (±1.6%) 162.99 (±0.4%)
117011
Bosnia and Herzegovina
596601 (±13.9%) 85.268 (±3.6%) 426.18 (±3.2%)
115370
Alberta, Canada
7442 (±1.4%) 13.650 (±2.3%) 107.84 (±0.3%)
103381
Algeria
14382 (±1.4%) 22.825 (±1.1%) 127.96 (±0.4%)
97616
China total, China total
87633 (±0.3%) 6.483 (±2.5%) 37.55 (±0.8%)
97020
Bahrain
96714 (±0.5%) 44.023 (±0.7%) 205.05 (±0.2%)
66635
Albania
15089229 (±48.5%) 151.388 (±4.4%) 808.60 (±5.5%)
60117
British Columbia, Canada
2630 (±0.7%) 15.149 (±1.4%) 93.32 (±0.3%)
53831
Afghanistan
42816 (±0.6%) 24.490 (±2.1%) 152.78 (±0.5%)
48630
Luxembourg
113473659 (±218.4%) 187.052 (±13.9%) 1037.09 (±18.7%)
36096
Estonia
15114864045 (±567.1%) 203.583 (±19.3%) 1258.53 (±26.7%)
27336
Cameroon
23625 (±0.5%) 33.021 (±1.3%) 164.91 (±0.4%)
27145
Manitoba, Canada
297 (±0.6%) 9.098 (±2.6%) 90.60 (±0.3%)
20556
Congo (Kinshasa)
13157 (±1.2%) 36.254 (±2.6%) 170.82 (±0.9%)
19715
Saskatchewan, Canada
7944722170 (±438.2%) 206.152 (±15.1%) 1269.16 (±21.0%)
18679
Angola
23592 (±2.1%) 45.581 (±1.7%) 293.88 (±0.5%)
17635
French Polynesia, France
60 (±0.4%) 9.439 (±1.5%) 84.77 (±0.2%)
17365
Botswana
32324 (±4.3%) 60.636 (±1.9%) 344.35 (±1.0%)
17096
Cuba
2024 (±0.3%) 12.960 (±0.5%) 104.44 (±0.1%)
14526
French Guiana, France
35340499 (±471.2%) 70.165 (±22.4%) 431.37 (±28.1%)
14065
Guinea
13821 (±0.6%) 43.558 (±1.0%) 181.44 (±0.4%)
12776
Cabo Verde
15840 (±0.9%) 53.996 (±0.7%) 268.11 (±0.3%)
11529
Belize
139999 (±24.0%) 90.554 (±4.4%) 490.81 (±4.1%)
8946
Andorra
805 (±0.6%) 10.434 (±2.2%) 88.66 (±0.3%)
8882
Burkina Faso
192985393 (±596.3%) 276.991 (±27.3%) 1570.63 (±39.4%)
8021
Bahamas
8461 (±0.6%) 34.898 (±0.9%) 257.50 (±0.1%)
7709
Congo (Brazzaville)
6055 (±0.7%) 35.313 (±1.4%) 196.56 (±0.4%)
6805
Guyana
7430 (±0.9%) 43.559 (±0.9%) 273.87 (±0.2%)
5057
New South Wales, Australia
3060 (±0.2%) 7.622 (±1.0%) 85.14 (±0.1%)
4973
Central African Republic
4855 (±0.1%) 18.203 (±0.6%) 160.52 (±0.1%)
3413
Benin
2999 (±0.8%) 36.448 (±1.7%) 188.23 (±0.5%)
2084
Guangdong, China
1762 (±0.6%) 14.283 (±4.6%) 30.58 (±6.3%)
1877
Eritrea
20407 (±98.8%) 147.489 (±15.2%) 670.71 (±20.2%)
1590
Shanghai, China
2280 (±7.0%) 92.286 (±4.7%) 221.89 (±7.3%)
1550
Nova Scotia, Canada
1138 (±0.6%) 12.932 (±4.1%) 101.20 (±0.7%)
1469
Comoros
640 (±1.4%) 41.349 (±2.7%) 184.15 (±0.9%)
1291
Queensland, Australia
1124 (±0.3%) 9.226 (±3.4%) 84.22 (±0.5%)
1150
Burundi
750 (±1.4%) 43.466 (±2.1%) 206.54 (±0.7%)
1036
Barbados
91 (±0.7%) 10.968 (±2.6%) 89.81 (±0.4%)
1031
Hebei, China
349 (±0.3%) 6.319 (±3.0%) 34.93 (±1.0%)
993
Anhui, China
992 (±0.0%) 4.598 (±0.4%) 33.03 (±0.1%)
886
Western Australia, Australia
696 (±0.8%) 15.794 (±4.2%) 88.74 (±1.3%)
837
Bhutan
750 (±4.4%) 62.335 (±2.8%) 277.81 (±1.8%)
688
Jiangsu, China
638 (±0.3%) 4.898 (±1.2%) 33.05 (±0.2%)
648
Faroe Islands, Denmark
187 (±0.1%) 6.271 (±0.9%) 79.23 (±0.1%)
591
Chongqing, China
578 (±0.4%) 4.917 (±1.2%) 30.77 (±0.3%)
529
Fujian, China
296 (±0.3%) 4.670 (±1.0%) 30.36 (±0.2%)
527
Shaanxi, China
246 (±0.2%) 4.647 (±0.8%) 31.37 (±0.2%)
450
Saint Vincent and the Grenadines
113 (±2.8%) 58.208 (±2.8%) 207.33 (±1.8%)
436
Cambodia
356 (±1.7%) 48.911 (±2.6%) 153.81 (±1.7%)
396
Liaoning, China
348 (±2.7%) 64.476 (±3.8%) 104.66 (±5.3%)
395
Newfoundland and Labrador, Canada
284 (±0.7%) 8.270 (±6.8%) 88.02 (±0.8%)
366
Inner Mongolia, China
293 (±0.8%) 31.049 (±2.4%) 83.82 (±2.0%)
327
Tianjin, China
193 (±0.8%) 14.415 (±3.4%) 36.95 (±3.1%)
266
Guangxi, China
257 (±0.1%) 5.373 (±0.9%) 31.54 (±0.2%)
266
Nunavut, Canada
267 (±1.0%) 14.677 (±2.4%) 326.31 (±0.1%)
234
Tasmania, Australia
230 (±0.1%) 11.041 (±1.0%) 94.10 (±0.2%)
227
Shanxi, China
133 (±0.4%) 4.329 (±1.5%) 31.54 (±0.3%)
184
Antigua and Barbuda
161 (±1.8%) 50.696 (±2.3%) 191.99 (±1.2%)
182
Gansu, China
168 (±0.6%) 21.190 (±3.3%) 35.45 (±6.3%)
174
Brunei
144 (±0.2%) 7.577 (±1.8%) 76.54 (±0.2%)
147
Guizhou, China
147 (±0.1%) 4.473 (±0.8%) 34.71 (±0.2%)
118
Australian Capital Territory, Australia
112 (±0.2%) 7.104 (±2.2%) 84.75 (±0.2%)
109
Dominica
23488788 (±785.1%) 301.861 (±29.6%) 1764.09 (±43.3%)
93
Northern Territory, Australia
45137 (±928.6%) 323.572 (±74.9%) 1595.50 (±111.6%)
70
Yukon, Canada
11 (±0.5%) 10.261 (±2.7%) 90.26 (±0.4%)
46
Macau, China
46 (±0.5%) 14.321 (±2.6%) 69.29 (±1.0%)
34
Saint Kitts and Nevis
1325099 (±3356.3%) 550.590 (±157.9%) 3019.10 (±237.9%)
25
Northwest Territories, Canada
3699558 (±1188.4%) 301.802 (±46.5%) 1752.67 (±67.9%)

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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