Laboratory at the Elm – Covid-19

COVID-19 Regional Numbers of Infected People

with Advanced Gompertz Function



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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 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: Sun Jan 17 05:25:59 UTC 2021

Ncurrent Nmax (fit) cumulative location cases daily t2 (fit) dturning point (fit)
83934927547549 (±0.9%) Brazil 46.200 (±1.1%) 220.56 (±0.4%)
17830471911191 (±0.5%) Argentina 45.217 (±0.5%) 268.07 (±0.1%)
700538107302 (±0.2%) Canada, Canada 17.896 (±0.4%) 112.45 (±0.1%)
526485494898 (±0.7%) Bangladesh 41.391 (±1.2%) 200.20 (±0.4%)
243286298734 (±0.9%) Lebanon 53.186 (±0.5%) 323.84 (±0.2%)
226866246793 (±1.1%) Ecuador 56.353 (±1.0%) 222.26 (±0.6%)
22654951281961178 (±492.5%) Azerbaijan 223.673 (±18.3%) 1345.76 (±25.7%)
221604789812 (±35.9%) Belarus 116.718 (±9.9%) 453.69 (±12.9%)
21150346522464676 (±458.8%) Bulgaria 201.704 (±17.4%) 1226.42 (±23.8%)
188969163090 (±0.8%) Dominican Republic 44.298 (±1.1%) 209.27 (±0.4%)
184187807 (±1.1%) Costa Rica 12.629 (±3.1%) 87.82 (±0.4%)
183589148953 (±0.2%) Bolivia 30.401 (±0.5%) 196.71 (±0.1%)
1639721006661 (±22.2%) Armenia 103.114 (±5.3%) 463.60 (±5.9%)
154620112265 (±0.5%) Egypt 26.535 (±1.6%) 162.99 (±0.4%)
117011596601 (±13.9%) Bosnia and Herzegovina 85.268 (±3.6%) 426.18 (±3.2%)
1153707442 (±1.4%) Alberta, Canada 13.650 (±2.3%) 107.84 (±0.3%)
10338114382 (±1.4%) Algeria 22.825 (±1.1%) 127.96 (±0.4%)
9761687633 (±0.3%) China total, China total 6.483 (±2.5%) 37.55 (±0.8%)
9702096714 (±0.5%) Bahrain 44.023 (±0.7%) 205.05 (±0.2%)
6663515089229 (±48.5%) Albania 151.388 (±4.4%) 808.60 (±5.5%)
601172630 (±0.7%) British Columbia, Canada 15.149 (±1.4%) 93.32 (±0.3%)
5383142816 (±0.6%) Afghanistan 24.490 (±2.1%) 152.78 (±0.5%)
48630113473659 (±218.4%) Luxembourg 187.052 (±13.9%) 1037.09 (±18.7%)
3609615114864045 (±567.1%) Estonia 203.583 (±19.3%) 1258.53 (±26.7%)
2733623625 (±0.5%) Cameroon 33.021 (±1.3%) 164.91 (±0.4%)
27145297 (±0.6%) Manitoba, Canada 9.098 (±2.6%) 90.60 (±0.3%)
2055613157 (±1.2%) Congo (Kinshasa) 36.254 (±2.6%) 170.82 (±0.9%)
197157944722170 (±438.2%) Saskatchewan, Canada 206.152 (±15.1%) 1269.16 (±21.0%)
1867923592 (±2.1%) Angola 45.581 (±1.7%) 293.88 (±0.5%)
1763560 (±0.4%) French Polynesia, France 9.439 (±1.5%) 84.77 (±0.2%)
1736532324 (±4.3%) Botswana 60.636 (±1.9%) 344.35 (±1.0%)
170962024 (±0.3%) Cuba 12.960 (±0.5%) 104.44 (±0.1%)
1452635340499 (±471.2%) French Guiana, France 70.165 (±22.4%) 431.37 (±28.1%)
1406513821 (±0.6%) Guinea 43.558 (±1.0%) 181.44 (±0.4%)
1277615840 (±0.9%) Cabo Verde 53.996 (±0.7%) 268.11 (±0.3%)
11529139999 (±24.0%) Belize 90.554 (±4.4%) 490.81 (±4.1%)
8946805 (±0.6%) Andorra 10.434 (±2.2%) 88.66 (±0.3%)
8882192985393 (±596.3%) Burkina Faso 276.991 (±27.3%) 1570.63 (±39.4%)
80218461 (±0.6%) Bahamas 34.898 (±0.9%) 257.50 (±0.1%)
77096055 (±0.7%) Congo (Brazzaville) 35.313 (±1.4%) 196.56 (±0.4%)
68057430 (±0.9%) Guyana 43.559 (±0.9%) 273.87 (±0.2%)
50573060 (±0.2%) New South Wales, Australia 7.622 (±1.0%) 85.14 (±0.1%)
49734855 (±0.1%) Central African Republic 18.203 (±0.6%) 160.52 (±0.1%)
34132999 (±0.8%) Benin 36.448 (±1.7%) 188.23 (±0.5%)
20841762 (±0.6%) Guangdong, China 14.283 (±4.6%) 30.58 (±6.3%)
187720407 (±98.8%) Eritrea 147.489 (±15.2%) 670.71 (±20.2%)
15902280 (±7.0%) Shanghai, China 92.286 (±4.7%) 221.89 (±7.3%)
15501138 (±0.6%) Nova Scotia, Canada 12.932 (±4.1%) 101.20 (±0.7%)
1469640 (±1.4%) Comoros 41.349 (±2.7%) 184.15 (±0.9%)
12911124 (±0.3%) Queensland, Australia 9.226 (±3.4%) 84.22 (±0.5%)
1150750 (±1.4%) Burundi 43.466 (±2.1%) 206.54 (±0.7%)
103691 (±0.7%) Barbados 10.968 (±2.6%) 89.81 (±0.4%)
1031349 (±0.3%) Hebei, China 6.319 (±3.0%) 34.93 (±1.0%)
993992 (±0.0%) Anhui, China 4.598 (±0.4%) 33.03 (±0.1%)
886696 (±0.8%) Western Australia, Australia 15.794 (±4.2%) 88.74 (±1.3%)
837750 (±4.4%) Bhutan 62.335 (±2.8%) 277.81 (±1.8%)
688638 (±0.3%) Jiangsu, China 4.898 (±1.2%) 33.05 (±0.2%)
648187 (±0.1%) Faroe Islands, Denmark 6.271 (±0.9%) 79.23 (±0.1%)
591578 (±0.4%) Chongqing, China 4.917 (±1.2%) 30.77 (±0.3%)
529296 (±0.3%) Fujian, China 4.670 (±1.0%) 30.36 (±0.2%)
527246 (±0.2%) Shaanxi, China 4.647 (±0.8%) 31.37 (±0.2%)
450113 (±2.8%) Saint Vincent and the Grenadines 58.208 (±2.8%) 207.33 (±1.8%)
436356 (±1.7%) Cambodia 48.911 (±2.6%) 153.81 (±1.7%)
396348 (±2.7%) Liaoning, China 64.476 (±3.8%) 104.66 (±5.3%)
395284 (±0.7%) Newfoundland and Labrador, Canada 8.270 (±6.8%) 88.02 (±0.8%)
366293 (±0.8%) Inner Mongolia, China 31.049 (±2.4%) 83.82 (±2.0%)
327193 (±0.8%) Tianjin, China 14.415 (±3.4%) 36.95 (±3.1%)
266257 (±0.1%) Guangxi, China 5.373 (±0.9%) 31.54 (±0.2%)
266267 (±1.0%) Nunavut, Canada 14.677 (±2.4%) 326.31 (±0.1%)
234230 (±0.1%) Tasmania, Australia 11.041 (±1.0%) 94.10 (±0.2%)
227133 (±0.4%) Shanxi, China 4.329 (±1.5%) 31.54 (±0.3%)
184161 (±1.8%) Antigua and Barbuda 50.696 (±2.3%) 191.99 (±1.2%)
182168 (±0.6%) Gansu, China 21.190 (±3.3%) 35.45 (±6.3%)
174144 (±0.2%) Brunei 7.577 (±1.8%) 76.54 (±0.2%)
147147 (±0.1%) Guizhou, China 4.473 (±0.8%) 34.71 (±0.2%)
118112 (±0.2%) Australian Capital Territory, Australia 7.104 (±2.2%) 84.75 (±0.2%)
10923488788 (±785.1%) Dominica 301.861 (±29.6%) 1764.09 (±43.3%)
9345137 (±928.6%) Northern Territory, Australia 323.572 (±74.9%) 1595.50 (±111.6%)
7011 (±0.5%) Yukon, Canada 10.261 (±2.7%) 90.26 (±0.4%)
4646 (±0.5%) Macau, China 14.321 (±2.6%) 69.29 (±1.0%)
341325099 (±3356.3%) Saint Kitts and Nevis 550.590 (±157.9%) 3019.10 (±237.9%)
253699558 (±1188.4%) Northwest Territories, Canada 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. The order of countries is by having its first case.
.·. Impressum