Labor am Elm

Elm Laboratory

Consulting and Research

COVID-19 Regional Numbers of Infected People

fit with advanced Gompertz function

Jens Röder

5 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.


If you like to support my work:
(by click on image you accept third party cookies, required by paypal)
For old broad desktop overview, follow this link.

Actualisation date: Thu Aug 5 04:23:09 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)
19985817
Brazil
29016702 (±1.8%) 107.608 (±1.1%) 417.99 (±0.9%)
4961880
Argentina
10303934 (±5.1%) 124.919 (±2.2%) 519.21 (±2.0%)
1296093
Bangladesh
1557622 (±5.6%) 119.949 (±3.5%) 407.79 (±3.4%)
487702
Ecuador
658199 (±1.4%) 105.393 (±1.1%) 382.75 (±0.8%)
475265
Bolivia
891513 (±5.5%) 129.337 (±2.7%) 484.45 (±2.7%)
448335
Belarus
569259 (±1.3%) 94.210 (±1.1%) 377.13 (±0.7%)
342850
Dominican Republic
369029 (±1.0%) 85.227 (±1.1%) 318.36 (±0.6%)
269495
Bahrain
859853 (±9.6%) 152.410 (±3.3%) 600.83 (±3.7%)
230713
Armenia
236226 (±0.6%) 66.027 (±1.0%) 296.08 (±0.4%)
175229
Algeria
14381 (±1.4%) 22.825 (±1.1%) 127.96 (±0.4%)
148572
Afghanistan
159490801 (±393.2%) 415.378 (±28.0%) 2144.28 (±40.5%)
133211
Albania
142046 (±0.5%) 55.167 (±1.0%) 352.15 (±0.2%)
115220
Botswana
617057 (±15.4%) 153.882 (±3.5%) 732.98 (±3.7%)
82064
Cameroon
239347 (±10.9%) 145.548 (±4.1%) 567.23 (±4.5%)
50529
Congo (Kinshasa)
1291052 (±200.5%) 56.726 (±14.6%) 320.11 (±18.1%)
43070
Angola
56026 (±3.1%) 98.389 (±2.2%) 415.19 (±1.4%)
33858
Cabo Verde
65973 (±4.4%) 119.125 (±2.2%) 487.80 (±1.9%)
15011
Bahamas
12616 (±1.3%) 67.591 (±2.0%) 297.41 (±0.8%)
14284
Belize
13191 (±0.3%) 40.518 (±1.1%) 312.12 (±0.2%)
13591
Burkina Faso
14029 (±0.7%) 48.181 (±1.7%) 342.98 (±0.3%)
13216
Congo (Brazzaville)
14467 (±1.4%) 87.649 (±1.5%) 313.05 (±0.9%)
9795
New South Wales, Australia
3060 (±0.2%) 7.622 (±1.0%) 85.14 (±0.1%)
8394
Benin
11363 (±2.6%) 96.146 (±2.1%) 370.86 (±1.4%)
7518
Burundi
16615 (±4.8%) 118.195 (±1.8%) 562.36 (±1.4%)
7151
Central African Republic
5632 (±0.8%) 26.698 (±4.0%) 164.79 (±1.0%)
6564
Eritrea
13280 (±5.1%) 111.116 (±2.3%) 521.37 (±1.7%)
5893
Nova Scotia, Canada
2888248762 (±791.2%) 488.453 (±28.0%) 2880.83 (±41.2%)
4588
Guinea-Bissau
4178 (±1.8%) 84.106 (±2.9%) 212.30 (±2.2%)
2532
Bhutan
143840 (±53.9%) 240.577 (±6.5%) 1175.45 (±8.5%)
1440
Newfoundland and Labrador, Canada
326678835 (±664.6%) 533.885 (±25.8%) 3083.35 (±38.1%)
1195
Saint Barthelemy, France
6 (±1.4%) 10.622 (±5.9%) 73.24 (±1.2%)
1158
Sichuan, China
6676271041 (±2693.4%) 1116.302 (±79.2%) 6623.41 (±122.4%)
1058
Western Australia, Australia
1019 (±1.1%) 71.357 (±2.9%) 95.96 (±5.4%)
1008
Anhui, China
994 (±0.0%) 4.617 (±0.5%) 33.05 (±0.1%)
987
Faroe Islands, Denmark
4095949923 (±2178.1%) 816.529 (±64.5%) 4863.46 (±98.8%)
657
Nunavut, Canada
877 (±4.1%) 84.630 (±4.0%) 409.71 (±1.5%)
610
Yukon, Canada
11 (±0.5%) 10.261 (±2.7%) 90.26 (±0.4%)
438
Liaoning, China
458 (±0.8%) 81.388 (±1.5%) 164.04 (±1.5%)
408
Inner Mongolia, China
384 (±0.6%) 60.315 (±1.8%) 110.27 (±2.4%)
338
Brunei
494007 (±730.4%) 669.903 (±52.4%) 3361.43 (±79.1%)
277
Guangxi, China
262 (±0.1%) 5.597 (±1.8%) 31.74 (±0.5%)
234
Tasmania, Australia
232 (±0.1%) 11.175 (±0.8%) 94.20 (±0.1%)
200
Northern Territory, Australia
506 (±8.0%) 145.385 (±3.1%) 548.50 (±3.5%)
147
Guizhou, China
147 (±0.0%) 4.474 (±0.6%) 34.71 (±0.1%)
124
Australian Capital Territory, Australia
116 (±0.2%) 7.952 (±3.0%) 85.07 (±0.3%)
63
Macau, China
48 (±0.4%) 15.544 (±2.6%) 69.48 (±1.1%)

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.


    • None
    • None

Recent posts

About

Elm Laboratory