Labor am Elm

Elm Laboratory

Consulting and Research

COVID-19 Regional Numbers of Dead People in the US

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: Tue Jun 15 06:02:16 UTC 2021

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Ncurrent
location
Nmax (err) cumulative_dead death rate (err) death_rate deaths_daily T2 (err) dturning_point (err)
9955
Queens, New York
7493 (±1.9%) 12.08 (±4.9%) 16.101 (±16.0%) 61.54 (±11.7%)
864
Burlington, New Jersey
2060 (±3853.4%) 11.15 (±8.2%) 383.693 (±1692.8%) 701.20 (±5460.0%)
834
Nueces, Texas
6885 (±2580.5%) 4.34 (±3.7%) 282.170 (±541.4%) 994.21 (±938.6%)
239
Jasper, Missouri
1059 (±19.2%) 6.08 (±4.8%) 100.529 (±4.5%) 469.72 (±4.7%)
223
Val Verde, Texas
144 (±0.8%) 9.11 (±2.8%) 31.253 (±1.9%) 227.22 (±0.3%)
199
Butte, California
1795 (±1540.5%) 5.35 (±6.8%) 194.051 (±252.0%) 813.82 (±370.2%)
195
Lea, New Mexico
27619 (±227.0%) 9.70 (±4.2%) 156.162 (±19.8%) 838.31 (±25.1%)
180
Santa Cruz, Arizona
525 (±877.2%) 6.26 (±22.5%) 198.441 (±252.1%) 634.20 (±434.4%)
174
Bonneville, Idaho
2744 (±28.7%) 3.90 (±4.8%) 97.841 (±4.3%) 536.56 (±4.3%)
171
Laurens, Georgia
4327 (±3797.6%) fiterr (±err) 311.708 (±562.4%) 1267.42 (±905.4%)
157
Limestone, Alabama
120 (±7.8%) fiterr (±err) 72.090 (±3.6%) 333.24 (±2.6%)
153
Crawford, Pennsylvania
177 (±9.7%) fiterr (±err) 33.394 (±4.2%) 358.28 (±0.8%)
151
San Patricio, Texas
87 (±0.6%) 9.23 (±2.7%) 24.561 (±2.0%) 225.31 (±0.2%)
150
Clearfield, Pennsylvania
396938 (±451.8%) fiterr (±err) 134.424 (±24.1%) 832.41 (±28.7%)
141
Vermilion, Illinois
106 (±95.4%) 3.99 (±20.6%) 35.011 (±67.9%) 329.42 (±11.8%)
138
Natrona, Wyoming
150 (±8.6%) 5.08 (±35.8%) 37.734 (±4.8%) 341.69 (±1.0%)
135
Muskingum, Ohio
765024 (±329.5%) 4.80 (±26.2%) 118.469 (±17.5%) 760.39 (±19.8%)
131
Phelps, Missouri
479 (±29.2%) 7.84 (±5.2%) 70.377 (±7.3%) 416.79 (±5.1%)
130
Anderson, Texas
64 (±1.9%) fiterr (±err) 44.805 (±2.1%) 256.70 (±0.6%)
125
Vermilion, Louisiana
1674 (±4750.4%) 5.59 (±3.0%) 351.527 (±851.6%) 1305.71 (±1459.1%)
123
Lonoke, Arkansas
190 (±4.9%) 6.26 (±5.3%) 58.139 (±2.0%) 353.08 (±1.0%)
120
Crawford, Arkansas
150 (±8.6%) 7.12 (±4.7%) 69.397 (±3.2%) 360.48 (±2.2%)
117
Laramie, Wyoming
693 (±47.7%) fiterr (±err) 69.103 (±8.9%) 446.81 (±6.2%)
116
El Dorado, California
98363 (±1203.9%) fiterr (±err) 181.094 (±66.5%) 1045.32 (±87.6%)
114
Dale, Alabama
57 (±0.8%) fiterr (±err) 28.597 (±2.3%) 219.60 (±0.3%)
108
Dyer, Tennessee
149 (±6.8%) 3.85 (±33.0%) 62.256 (±3.0%) 339.48 (±1.7%)
106
Jim Wells, Texas
65 (±1.1%) 7.42 (±5.0%) 37.937 (±1.9%) 244.03 (±0.3%)
105
Roane, Tennessee
583 (±41.3%) 6.86 (±6.1%) 74.241 (±7.9%) 452.48 (±6.0%)
103
Hockley, Texas
210 (±184.8%) 6.52 (±24.6%) 54.811 (±70.7%) 360.64 (±33.0%)
101
Morton, North Dakota
91 (±23.1%) 2.75 (±5.3%) 34.550 (±30.2%) 280.96 (±4.5%)
100
Lawrence, Alabama
38 (±0.9%) fiterr (±err) 25.607 (±2.2%) 258.00 (±0.2%)
98
Benton, Minnesota
97 (±46.7%) fiterr (±err) 30.338 (±42.3%) 324.33 (±5.1%)
97
Beaufort, North Carolina
64 (±1.0%) 7.19 (±3.1%) 33.930 (±1.5%) 273.10 (±0.2%)
96
Smyth, Virginia
79 (±8.2%) 9.44 (±3.4%) 52.972 (±4.8%) 314.03 (±2.0%)
94
Lawrence, Tennessee
220594 (±778.4%) 5.55 (±4.2%) 196.969 (±46.8%) 1100.40 (±63.2%)
93
Gibson, Indiana
902 (±433.8%) 4.75 (±19.2%) 79.401 (±79.7%) 467.47 (±64.7%)
91
Wayne, Georgia
55 (±3.0%) 6.54 (±4.0%) 42.591 (±4.1%) 249.11 (±0.9%)
90
Okeechobee, Florida
53 (±1.1%) 5.19 (±44.2%) 38.160 (±1.5%) 252.47 (±0.3%)
89
Simpson, Mississippi
57 (±4.3%) fiterr (±err) 35.839 (±8.6%) 211.11 (±1.9%)
88
Scotland, North Carolina
240 (±88.9%) fiterr (±err) 84.261 (±24.8%) 413.81 (±22.1%)
87
Petersburg, Virginia
29 (±5.6%) 12.32 (±28.8%) 4.982 (±45619838705.7%) 34.98 (±261538047303.2%)
86
Warren, Tennessee
261906 (±497.0%) 5.64 (±5.9%) 199.275 (±27.4%) 1133.49 (±37.0%)
85
Douglas, Kansas
82 (±10.9%) fiterr (±err) 74.590 (±4.5%) 354.29 (±3.3%)
84
Curry, New Mexico
16011398 (±395.3%) fiterr (±err) 200.581 (±14.2%) 1232.11 (±19.5%)
83
Codington, South Dakota
108 (±5.7%) 2.05 (±63.6%) 37.184 (±3.9%) 329.24 (±0.8%)
81
Geneva, Alabama
50123 (±614.5%) fiterr (±err) 190.446 (±39.1%) 1059.80 (±52.2%)
80
Boone, Arkansas
75 (±3.4%) 5.90 (±6.0%) 40.752 (±3.0%) 296.72 (±0.7%)
78
Franklin, Illinois
156 (±8.4%) 5.99 (±6.2%) 56.839 (±2.7%) 378.12 (±1.4%)
77
Greene, Arkansas
672 (±47.2%) fiterr (±err) 95.931 (±8.6%) 504.22 (±8.4%)
76
Big Horn, Montana
855 (±286.1%) 4.07 (±8.5%) 135.282 (±52.7%) 598.86 (±67.5%)
75
Rhea, Tennessee
93 (±6.1%) fiterr (±err) 58.804 (±2.9%) 336.34 (±1.5%)
74
Hot Spring, Arkansas
60 (±2.7%) 4.25 (±7.2%) 47.280 (±2.8%) 259.90 (±0.9%)
73
Harrison, Iowa
117 (±11.1%) 5.09 (±27.7%) 49.099 (±5.0%) 348.41 (±1.9%)
72
Catoosa, Georgia
113 (±18.9%) fiterr (±err) 97.012 (±7.0%) 382.19 (±7.5%)
70
Henry, Illinois
178009 (±1330.7%) fiterr (±err) 152.617 (±76.6%) 902.63 (±95.9%)
69
Newaygo, Michigan
15004277 (±972.5%) fiterr (±err) 174.810 (±34.3%) 1099.72 (±45.7%)
68
Tattnall, Georgia
81 (±9.5%) 6.75 (±13.6%) 63.126 (±4.2%) 341.71 (±2.5%)
67
Tishomingo, Mississippi
44 (±0.7%) 4.12 (±34.8%) 22.146 (±2.5%) 232.80 (±0.3%)
66
Liberty, Georgia
29 (±8.2%) fiterr (±err) 27.799 (±20.5%) 234.46 (±2.8%)
65
Hardeman, Tennessee
41 (±1.1%) fiterr (±err) 37.643 (±1.8%) 226.05 (±0.4%)
64
Van Wert, Ohio
8869939 (±712.1%) fiterr (±err) 168.627 (±27.9%) 1048.81 (±36.5%)
63
Tehama, California
53 (±96.8%) 5.53 (±5.2%) 43.219 (±63.3%) 320.95 (±17.2%)
62
Scurry, Texas
36 (±2.6%) 4.47 (±27.6%) 39.362 (±2.3%) 301.93 (±0.5%)
61
O’Brien, Iowa
96468 (±941.4%) fiterr (±err) 168.652 (±62.4%) 947.56 (±80.8%)
60
Perry, Illinois
5365 (±274.5%) fiterr (±err) 150.650 (±28.3%) 779.68 (±35.7%)
58
Lincoln, Kentucky
21 (±18.6%) 16.65 (±6.1%) 26.913 (±44.9%) 248.71 (±5.3%)
57
Hart, Georgia
61 (±10.7%) fiterr (±err) 66.958 (±5.9%) 316.16 (±3.6%)
56
Lee, Iowa
627 (±531.3%) fiterr (±err) 140.624 (±79.9%) 660.73 (±101.6%)
55
Fayette, Illinois
73 (±73.2%) 2.39 (±18.9%) 48.919 (±43.8%) 319.53 (±15.6%)
53
Cherokee, Kansas
315 (±228.9%) fiterr (±err) 118.234 (±36.7%) 582.83 (±42.0%)
52
Clay, Arkansas
1520 (±48.0%) 6.97 (±12.5%) 137.407 (±6.1%) 687.20 (±7.5%)
51
Amador, California
17 (±1.3%) 10.14 (±5.3%) 12.475 (±9.1%) 224.61 (±0.4%)
50
Randolph, Arkansas
39 (±2.6%) 6.14 (±4.9%) 40.838 (±3.3%) 252.16 (±0.8%)
49
Fentress, Tennessee
38 (±3.5%) 3.25 (±5.6%) 38.679 (±2.8%) 311.91 (±0.6%)
48
Warren, Illinois
79 (±6.9%) fiterr (±err) 52.592 (±2.8%) 356.59 (±1.2%)
47
Fulton, Arkansas
17279 (±534.1%) 6.69 (±10.9%) 140.078 (±42.3%) 793.56 (±50.8%)
46
Berrien, Georgia
258 (±195.2%) fiterr (±err) 105.331 (±43.5%) 485.88 (±47.8%)
45
Gulf, Florida
37 (±13.8%) 4.82 (±4.4%) 61.485 (±10.3%) 282.80 (±5.1%)
44
Gilchrist, Florida
21 (±1.1%) 7.84 (±14.4%) 33.714 (±2.3%) 237.79 (±0.3%)
43
Clay, Illinois
55 (±20.0%) 7.12 (±9.0%) 50.202 (±12.0%) 331.66 (±4.0%)
42
Bonner, Idaho
22 (±14.2%) 10.45 (±6.6%) 31.702 (±8.6%) 343.56 (±1.3%)
41
Chicot, Arkansas
36 (±8.5%) 3.15 (±31.9%) 49.650 (±8.7%) 248.62 (±3.2%)
40
Franklin, Arkansas
40 (±9.6%) 7.65 (±7.8%) 32.349 (±6.3%) 338.30 (±1.0%)
39
Gem, Idaho
54232 (±717.3%) 8.24 (±7.2%) 154.556 (±44.3%) 899.83 (±55.5%)
38
Arkansas, Arkansas
35 (±3.1%) 6.77 (±5.1%) 42.357 (±2.8%) 293.59 (±0.7%)
37
Siskiyou, California
11 (±4.5%) fiterr (±err) 19.696 (±5.6%) 336.32 (±0.3%)
36
Douglas, Illinois
1686228 (±531.0%) fiterr (±err) 246.144 (±22.7%) 1434.55 (±32.1%)
35
Ashley, Arkansas
84 (±122.8%) fiterr (±err) 108.428 (±36.6%) 437.36 (±42.9%)
34
Greene, Illinois
36 (±4.0%) fiterr (±err) 38.037 (±4.4%) 288.64 (±0.8%)
33
Grant, Arkansas
12122 (±426.5%) fiterr (±err) 163.163 (±31.0%) 908.57 (±39.4%)
32
Treutlen, Georgia
17 (±1.7%) fiterr (±err) 41.220 (±2.1%) 254.60 (±0.5%)
31
Evans, Georgia
19 (±7.2%) 4.84 (±11.8%) 51.210 (±6.1%) 279.74 (±2.2%)
30
Marion, Arkansas
155514 (±623.7%) 4.70 (±14.8%) 113.126 (±34.0%) 733.92 (±37.4%)
29
De Witt, Illinois
313337 (±766.1%) 3.77 (±44.5%) 176.329 (±39.1%) 1039.48 (±51.2%)
28
Moultrie, Illinois
1046 (±117.4%) 4.02 (±12.0%) 125.177 (±14.5%) 657.56 (±16.7%)
27
Perry, Alabama
9 (±5.5%) fiterr (±err) 52.793 (±7.4%) 219.81 (±2.3%)
26
Newton, Arkansas
23 (±1.0%) 4.35 (±23.0%) 27.271 (±3.2%) 224.03 (±0.4%)
25
Howard, Arkansas
17 (±1.1%) fiterr (±err) 35.386 (±1.8%) 247.03 (±0.3%)
24
Desha, Arkansas
12 (±3.7%) fiterr (±err) 49.326 (±3.9%) 254.91 (±1.3%)
23
Madison, Arkansas
51 (±29.2%) 6.79 (±15.4%) 87.986 (±8.2%) 420.38 (±7.6%)
22
Pike, Arkansas
6192358 (±2495.9%) 7.94 (±6.5%) 191.017 (±83.3%) 1195.50 (±113.8%)
21
Carroll, Kentucky
6 (±1.7%) 7.41 (±60.2%) 35.048 (±3.6%) 221.25 (±0.7%)
20
Franklin, Florida
4 (±0.9%) 1.78 (±64.4%) 25.689 (±3.6%) 212.16 (±0.5%)
19
Faribault, Minnesota
20 (±17.5%) fiterr (±err) 27.911 (±8.9%) 355.30 (±1.2%)
18
Swain, North Carolina
22 (±39.2%) 8.28 (±56.4%) 103.114 (±13.9%) 400.99 (±15.6%)
16
Madison, Virginia
4 (±7.4%) 18.63 (±16.8%) 4.983 (±107188528794.5%) 53.94 (±312688433320.4%)

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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