Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Netherlands of about 2.31% each day. That corresponds to a doubling of the numbers approx. every 30 days.
The graph above and the following table show the course of reported coronavirus infections in Netherlands assuming that the numbers are following an exponential trend without any slowdown.
28,300

29,400
+1,070 (+3.77%)
30,600
+1,240 (+4.21%)
31,800
+1,150 (+3.75%)
32,800
+1,070 (+3.37%)
33,600
+750 (+2.28%)
34,300
+729 (+2.17%)
35,000
+715 (+2.08%)
35,900
+889 (+2.54%)
36,700
+808 (+2.25%)
37,600
37,500  37,600
+849 (+2.31%)
38,400
38,400  38,500
+870 (+2.31%)
39,300
39,300  39,400
+890 (+2.31%)
40,200
40,200  40,300
+911 (+2.31%)
41,200
41,100  41,300
+932 (+2.31%)
42,100
42,100  42,200
+953 (+2.31%)
43,100
43,000  43,200
+975 (+2.31%)
44,100
44,000  44,200
+998 (+2.31%)
45,100
45,000  45,200
+1,020 (+2.31%)
46,200
46,100  46,300
+1,040 (+2.31%)
Using loglinear regression on the data of the previous days, we could infer an increase of reported deaths by coronavirus in Netherlands of about 3.08% each day. That corresponds to a doubling of the numbers approx. every 23 days.
The graph above and the following table show the course of reported deaths by coronavirus in Netherlands assuming that the numbers are following an exponential trend without any slowdown.
3,150

3,330
+182 (+5.79%)
3,470
+144 (+4.33%)
3,610
+142 (+4.09%)
3,700
+84 (+2.32%)
3,760
+67 (+1.81%)
3,930
+165 (+4.38%)
4,070
+139 (+3.54%)
4,190
+124 (+3.05%)
4,300
+112 (+2.67%)
4,450
4,430  4,460
+142 (+3.29%)
4,580
4,560  4,600
+137 (+3.08%)
4,720
4,700  4,740
+141 (+3.08%)
4,870
4,850  4,890
+146 (+3.08%)
5,020
5,000  5,040
+150 (+3.08%)
5,170
5,150  5,200
+155 (+3.08%)
5,330
5,310  5,360
+159 (+3.08%)
5,500
5,470  5,520
+164 (+3.08%)
5,670
5,640  5,690
+169 (+3.08%)
5,840
5,820  5,870
+175 (+3.08%)
In Netherlands, approx. 0.89% of the population die each year. With a population of roughly 17,200,000 people in Netherlands, that corresponds to about 420 deaths per day on the statistical average.
The graph above shows the reported daily deaths by coronavirus in contrast to the statistical number as baseline.
To estimate the mortality rate of coronavirus infections, we need to consider that a reported death already showed up in the reported cases a few days before. It is presumed that this lag is between 7 and 14 days. If we assumed that the lag was about 7 days, the mortality rate in Netherlands would be approx. 14%.
The graph aboves shows the mortality depending on different presumed lag.
The graph above shows the daily increase of reported coronavirus infections in Netherlands in the previous days.
The graph shows the daily increase of reported deaths by coronavirus in Netherlands in the previous days.
The graph tries to predict the number of required intensive care units in Netherlands. We assume the following:
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Aruba of about 0.918% each day. That corresponds to a doubling of the numbers approx. every 76 days.
The graph above and the following table show the course of reported coronavirus infections in Aruba assuming that the numbers are following an exponential trend without any slowdown.
93

95
+2 (+2.15%)
96
+1 (+1.05%)
96
+0 (+0%)
97
+1 (+1.04%)
97
+0 (+0%)
97
+0 (+0%)
100
+3 (+3.09%)
100
+0 (+0%)
100
+0 (+0%)
102
100  103
+2 (+1.53%)
102
101  104
+0 (+0.918%)
103
102  105
+0 (+0.918%)
104
103  106
+0 (+0.918%)
105
104  107
+0 (+0.918%)
106
105  108
+0 (+0.918%)
107
105  109
+0 (+0.918%)
108
106  110
+0 (+0.918%)
109
107  111
+0 (+0.918%)
110
108  112
+1 (+0.918%)
Using loglinear regression on the data of the previous days, we could infer an increase of reported deaths by coronavirus in Aruba of about 1.46e10% each day. That corresponds to a doubling of the numbers approx. every ,480,000,000,000 days.
The graph above and the following table show the course of reported deaths by coronavirus in Aruba assuming that the numbers are following an exponential trend without any slowdown.
1

2
+1 (+100%)
2
+0 (+0%)
2
+0 (+0%)
2
+0 (+0%)
2
+0 (+0%)
2
+0 (+0%)
2
+0 (+0%)
2
+0 (+0%)
2
+0 (+0%)
2
2  2
+0 (+3.64e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
To estimate the mortality rate of coronavirus infections, we need to consider that a reported death already showed up in the reported cases a few days before. It is presumed that this lag is between 7 and 14 days. If we assumed that the lag was about 7 days, the mortality rate in Aruba would be approx. 2.1%.
The graph aboves shows the mortality depending on different presumed lag.
The graph above shows the daily increase of reported coronavirus infections in Aruba in the previous days.
The graph shows the daily increase of reported deaths by coronavirus in Aruba in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Bonaire, Sint Eustatius and Saba of about 2.91e10% each day. That corresponds to a doubling of the numbers approx. every ,240,000,000,000 days.
The graph above and the following table show the course of reported coronavirus infections in Bonaire, Sint Eustatius and Saba assuming that the numbers are following an exponential trend without any slowdown.
3

3
+0 (+0%)
3
+0 (+0%)
3
+0 (+0%)
5
+2 (+66.7%)
5
+0 (+0%)
5
+0 (+0%)
5
+0 (+0%)
5
+0 (+0%)
5
+0 (+0%)
5
5  5
+0 (+7.28e10%)
5
5  5
+0 (+2.91e10%)
5
5  5
+0 (+2.91e10%)
5
5  5
+0 (+2.91e10%)
5
5  5
+0 (+2.91e10%)
5
5  5
+0 (+2.91e10%)
5
5  5
+0 (+2.91e10%)
5
5  5
+0 (+2.91e10%)
5
5  5
+0 (+2.91e10%)
5
5  5
+0 (+2.91e10%)
The graph above and the following table show the course of reported deaths by coronavirus in Bonaire, Sint Eustatius and Saba assuming that the numbers are following an exponential trend without any slowdown.
0

0
+0 (+0%)
0
+0 (+0%)
0
+0 (+0%)
0
+0 (+0%)
0
+0 (+0%)
0
+0 (+0%)
0
+0 (+0%)
0
+0 (+0%)
0
+0 (+0%)
To estimate the mortality rate of coronavirus infections, we need to consider that a reported death already showed up in the reported cases a few days before. It is presumed that this lag is between 7 and 14 days. If we assumed that the lag was about 7 days, the mortality rate in Bonaire, Sint Eustatius and Saba would be approx. 0%.
The graph aboves shows the mortality depending on different presumed lag.
The graph above shows the daily increase of reported coronavirus infections in Bonaire, Sint Eustatius and Saba in the previous days.
The graph shows the daily increase of reported deaths by coronavirus in Bonaire, Sint Eustatius and Saba in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Curacao of about 4.09% each day. That corresponds to a doubling of the numbers approx. every 17 days.
The graph above and the following table show the course of reported coronavirus infections in Curacao assuming that the numbers are following an exponential trend without any slowdown.
14

14
+0 (+0%)
14
+0 (+0%)
14
+0 (+0%)
14
+0 (+0%)
14
+0 (+0%)
14
+0 (+0%)
14
+0 (+0%)
14
+0 (+0%)
16
+2 (+14.3%)
16
15  17
+0 (+3.76e10%)
17
15  18
+0 (+4.09%)
17
16  19
+0 (+4.09%)
18
17  19
+0 (+4.09%)
19
17  20
+0 (+4.09%)
20
18  21
+0 (+4.09%)
20
19  22
+0 (+4.09%)
21
20  23
+0 (+4.09%)
22
20  24
+0 (+4.09%)
23
21  25
+0 (+4.09%)
The graph above and the following table show the course of reported deaths by coronavirus in Curacao assuming that the numbers are following an exponential trend without any slowdown.
1

1
+0 (+0%)
1
+0 (+0%)
1
+0 (+0%)
1
+0 (+0%)
1
+0 (+0%)
1
+0 (+0%)
1
+0 (+0%)
1
+0 (+0%)
1
+0 (+0%)
To estimate the mortality rate of coronavirus infections, we need to consider that a reported death already showed up in the reported cases a few days before. It is presumed that this lag is between 7 and 14 days. If we assumed that the lag was about 7 days, the mortality rate in Curacao would be approx. 7.1%.
The graph aboves shows the mortality depending on different presumed lag.
The graph above shows the daily increase of reported coronavirus infections in Curacao in the previous days.
The graph shows the daily increase of reported deaths by coronavirus in Curacao in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Netherlands of about 19.7% each day. That corresponds to a doubling of the numbers approx. every 3.8 days.
The graph above and the following table show the course of reported coronavirus infections in Netherlands assuming that the numbers are following an exponential trend without any slowdown.
1,410

1,710
+292 (+20.7%)
2,050
+346 (+20.3%)
2,460
+409 (+19.9%)
2,990
+534 (+21.7%)
3,630
+637 (+21.3%)
4,200
+573 (+15.8%)
5,110
4,970  5,250
+903 (+21.5%)
6,120
5,950  6,280
+1,010 (+19.7%)
7,320
7,130  7,520
+1,210 (+19.7%)
8,770
8,530  9,000
+1,440 (+19.7%)
10,500
10,200  10,800
+1,730 (+19.7%)
12,600
12,200  12,900
+2,070 (+19.7%)
15,000
14,600  15,500
+2,480 (+19.7%)
18,000
17,500  18,500
+2,970 (+19.7%)
21,600
21,000  22,200
+3,550 (+19.7%)
25,800
25,100  26,500
+4,250 (+19.7%)
Using loglinear regression on the data of the previous days, we could infer an increase of reported deaths by coronavirus in Netherlands of about 32.6% each day. That corresponds to a doubling of the numbers approx. every 2.5 days.
The graph above and the following table show the course of reported deaths by coronavirus in Netherlands assuming that the numbers are following an exponential trend without any slowdown.
24

43
+19 (+79.2%)
58
+15 (+34.9%)
76
+18 (+31%)
106
+30 (+39.5%)
136
+30 (+28.3%)
179
+43 (+31.6%)
239
231  249
+60 (+33.8%)
317
306  330
+78 (+32.6%)
421
405  437
+103 (+32.6%)
558
537  579
+137 (+32.6%)
740
712  768
+182 (+32.6%)
980
944  1,020
+241 (+32.6%)
1,300
1,250  1,350
+319 (+32.6%)
1,720
1,660  1,790
+423 (+32.6%)
2,280
2,200  2,370
+561 (+32.6%)
3,030
2,920  3,140
+744 (+32.6%)
To estimate the mortality rate of coronavirus infections, we need to consider that a reported death already showed up in the reported cases a few days before. It is presumed that this lag is between 7 and 14 days.
The graph aboves shows the mortality depending on different presumed lag.
The graph above shows the daily increase of reported coronavirus infections in Netherlands in the previous days.
The graph shows the daily increase of reported deaths by coronavirus in Netherlands in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Sint Maarten of about 2.89% each day. That corresponds to a doubling of the numbers approx. every 24 days.
The graph above and the following table show the course of reported coronavirus infections in Sint Maarten assuming that the numbers are following an exponential trend without any slowdown.
53

57
+4 (+7.55%)
57
+0 (+0%)
64
+7 (+12.3%)
67
+3 (+4.69%)
67
+0 (+0%)
67
+0 (+0%)
71
+4 (+5.97%)
73
+2 (+2.82%)
73
+0 (+0%)
76
74  78
+3 (+4.38%)
78
76  81
+2 (+2.89%)
81
78  83
+2 (+2.89%)
83
81  85
+2 (+2.89%)
85
83  88
+2 (+2.89%)
88
85  90
+2 (+2.89%)
90
88  93
+3 (+2.89%)
93
90  96
+3 (+2.89%)
96
93  99
+3 (+2.89%)
98
96  101
+3 (+2.89%)
Using loglinear regression on the data of the previous days, we could infer an increase of reported deaths by coronavirus in Sint Maarten of about 6.55% each day. That corresponds to a doubling of the numbers approx. every 11 days.
The graph above and the following table show the course of reported deaths by coronavirus in Sint Maarten assuming that the numbers are following an exponential trend without any slowdown.
9

9
+0 (+0%)
9
+0 (+0%)
9
+0 (+0%)
10
+1 (+11.1%)
10
+0 (+0%)
10
+0 (+0%)
11
+1 (+10%)
12
+1 (+9.09%)
12
+0 (+0%)
13
12  14
+1 (+9.54%)
14
13  15
+0 (+6.55%)
15
14  16
+0 (+6.55%)
16
15  17
+0 (+6.55%)
17
16  18
+1 (+6.55%)
18
17  19
+1 (+6.55%)
19
18  20
+1 (+6.55%)
20
19  22
+1 (+6.55%)
22
21  23
+1 (+6.55%)
23
22  24
+1 (+6.55%)
To estimate the mortality rate of coronavirus infections, we need to consider that a reported death already showed up in the reported cases a few days before. It is presumed that this lag is between 7 and 14 days. If we assumed that the lag was about 7 days, the mortality rate in Sint Maarten would be approx. 21%.
The graph aboves shows the mortality depending on different presumed lag.
The graph above shows the daily increase of reported coronavirus infections in Sint Maarten in the previous days.
The graph shows the daily increase of reported deaths by coronavirus in Sint Maarten in the previous days.
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